librarian-bots/model_cards_with_metadata · Datasets at Hugging Face

modelId stringlengths 5 139	author stringlengths 2 42	last_modified timestamp[us, tz=UTC]date 2020-02-15 11:33:14 2025-07-14 00:44:55	downloads int64 0 223M	likes int64 0 11.7k	library_name stringclasses 519 values	tags listlengths 1 4.05k	pipeline_tag stringclasses 55 values	createdAt timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2025-07-14 00:44:41	card stringlengths 11 1.01M
jonatasgrosman/exp_w2v2t_it_vp-100k_s449	jonatasgrosman	2022-07-08T19:01:30Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T19:00:43Z	--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-100k_s449 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-100k_s149	jonatasgrosman	2022-07-08T18:56:07Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T18:55:24Z	--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-100k_s149 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
domenicrosati/SPECTER-with-biblio-context-finetuned-review_classifier	domenicrosati	2022-07-08T18:53:09Z	27	0	transformers	[ "transformers", "pytorch", "bert", "text-classification", "generated_from_trainer", "license:apache-2.0", "endpoints_compatible", "region:us" ]	text-classification	2022-07-08T13:43:12Z	--- license: apache-2.0 tags: - text-classification - generated_from_trainer metrics: - accuracy - f1 - recall - precision model-index: - name: SPECTER-with-biblio-context-finetuned-review_classifier results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # SPECTER-with-biblio-context-finetuned-review_classifier This model is a fine-tuned version of [allenai/specter](https://huggingface.co/allenai/specter) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1284 - Accuracy: 0.962 - F1: 0.7892 - Recall: 0.7593 - Precision: 0.8216 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 4.5e-05 - train_batch_size: 12 - eval_batch_size: 12 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 1000 - num_epochs: 2 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| F1 \| Recall \| Precision \| \|:-------------:\|:-----:\|:-----:\|:---------------:\|:--------:\|:------:\|:------:\|:---------:\| \| 0.1956 \| 1.0 \| 6667 \| 0.1805 \| 0.9514 \| 0.7257 \| 0.6860 \| 0.7702 \| \| 0.135 \| 2.0 \| 13334 \| 0.1284 \| 0.962 \| 0.7892 \| 0.7593 \| 0.8216 \| ### Framework versions - Transformers 4.20.1 - Pytorch 1.12.0+cu102 - Datasets 2.3.2 - Tokenizers 0.12.1
saekomdalkom/long-t5-local-base-finetuned	saekomdalkom	2022-07-08T18:48:45Z	5	0	transformers	[ "transformers", "pytorch", "longt5", "text2text-generation", "generated_from_trainer", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text2text-generation	2022-07-01T05:40:08Z	--- license: apache-2.0 tags: - generated_from_trainer metrics: - rouge model-index: - name: long-t5-local-base-finetuned results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # long-t5-local-base-finetuned This model is a fine-tuned version of [google/long-t5-local-base](https://huggingface.co/google/long-t5-local-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 9.2722 - Rouge1: 3.8848 - Rouge2: 0.5914 - Rougel: 3.5038 - Rougelsum: 3.7022 - Gen Len: 19.0 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-06 - train_batch_size: 3 - eval_batch_size: 3 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50000 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rouge1 \| Rouge2 \| Rougel \| Rougelsum \| Gen Len \| \|:-------------:\|:-----:\|:-----:\|:---------------:\|:------:\|:------:\|:------:\|:---------:\|:-------:\| \| No log \| 0.16 \| 100 \| 342.4395 \| 0.0 \| 0.0 \| 0.0 \| 0.0 \| 19.0 \| \| No log \| 0.31 \| 200 \| 323.6985 \| 0.0 \| 0.0 \| 0.0 \| 0.0 \| 19.0 \| \| No log \| 0.47 \| 300 \| 303.8767 \| 0.0 \| 0.0 \| 0.0 \| 0.0 \| 19.0 \| \| No log \| 0.62 \| 400 \| 284.7559 \| 0.0 \| 0.0 \| 0.0 \| 0.0 \| 19.0 \| \| 295.8376 \| 0.78 \| 500 \| 263.0420 \| 0.0 \| 0.0 \| 0.0 \| 0.0 \| 19.0 \| \| 295.8376 \| 0.93 \| 600 \| 243.2220 \| 0.0242 \| 0.0 \| 0.0223 \| 0.0242 \| 19.0 \| \| 295.8376 \| 1.09 \| 700 \| 224.4514 \| 0.0493 \| 0.0 \| 0.0507 \| 0.0513 \| 19.0 \| \| 295.8376 \| 1.24 \| 800 \| 203.9065 \| 0.0656 \| 0.0 \| 0.0634 \| 0.0658 \| 19.0 \| \| 295.8376 \| 1.4 \| 900 \| 184.8686 \| 0.0609 \| 0.0 \| 0.058 \| 0.0616 \| 19.0 \| \| 199.938 \| 1.55 \| 1000 \| 167.5315 \| 0.0638 \| 0.0 \| 0.0626 \| 0.063 \| 19.0 \| \| 199.938 \| 1.71 \| 1100 \| 151.2369 \| 0.0421 \| 0.0 \| 0.0411 \| 0.0413 \| 19.0 \| \| 199.938 \| 1.86 \| 1200 \| 137.2366 \| 0.0358 \| 0.0 \| 0.0346 \| 0.0342 \| 19.0 \| \| 199.938 \| 2.02 \| 1300 \| 125.3076 \| 0.0173 \| 0.0 \| 0.0157 \| 0.0157 \| 19.0 \| \| 199.938 \| 2.17 \| 1400 \| 114.5600 \| 0.0173 \| 0.0 \| 0.0157 \| 0.0157 \| 19.0 \| \| 136.1309 \| 2.33 \| 1500 \| 105.9237 \| 0.0361 \| 0.0 \| 0.0344 \| 0.0363 \| 19.0 \| \| 136.1309 \| 2.48 \| 1600 \| 97.4123 \| 0.0526 \| 0.0 \| 0.051 \| 0.054 \| 19.0 \| \| 136.1309 \| 2.64 \| 1700 \| 89.0873 \| 0.0427 \| 0.0 \| 0.0407 \| 0.0418 \| 19.0 \| \| 136.1309 \| 2.79 \| 1800 \| 82.0562 \| 0.0496 \| 0.0 \| 0.0462 \| 0.0462 \| 19.0 \| \| 136.1309 \| 2.95 \| 1900 \| 76.2360 \| 0.0361 \| 0.0 \| 0.0345 \| 0.0363 \| 19.0 \| \| 99.2229 \| 3.1 \| 2000 \| 70.0604 \| 0.0438 \| 0.0 \| 0.0425 \| 0.0439 \| 19.0 \| \| 99.2229 \| 3.26 \| 2100 \| 65.1038 \| 0.0454 \| 0.0 \| 0.0441 \| 0.0447 \| 19.0 \| \| 99.2229 \| 3.41 \| 2200 \| 59.1831 \| 0.0344 \| 0.0 \| 0.0318 \| 0.0318 \| 19.0 \| \| 99.2229 \| 3.57 \| 2300 \| 53.0313 \| 0.0471 \| 0.0 \| 0.0448 \| 0.0454 \| 19.0 \| \| 99.2229 \| 3.72 \| 2400 \| 48.2110 \| 0.0369 \| 0.0 \| 0.0369 \| 0.0369 \| 19.0 \| \| 73.4208 \| 3.88 \| 2500 \| 44.2004 \| 0.0425 \| 0.0 \| 0.0427 \| 0.044 \| 19.0 \| \| 73.4208 \| 4.03 \| 2600 \| 40.1925 \| 0.0632 \| 0.0 \| 0.0619 \| 0.0612 \| 19.0 \| \| 73.4208 \| 4.19 \| 2700 \| 36.3698 \| 0.0887 \| 0.0 \| 0.0873 \| 0.086 \| 19.0 \| \| 73.4208 \| 4.34 \| 2800 \| 33.2154 \| 0.164 \| 0.0 \| 0.1652 \| 0.1705 \| 19.0 \| \| 73.4208 \| 4.5 \| 2900 \| 30.9366 \| 0.1106 \| 0.0 \| 0.1138 \| 0.1144 \| 19.0 \| \| 55.6661 \| 4.65 \| 3000 \| 28.5672 \| 0.1289 \| 0.0 \| 0.1295 \| 0.131 \| 19.0 \| \| 55.6661 \| 4.81 \| 3100 \| 27.0910 \| 0.2501 \| 0.0 \| 0.2514 \| 0.2527 \| 19.0 \| \| 55.6661 \| 4.96 \| 3200 \| 25.6666 \| 0.318 \| 0.0 \| 0.3322 \| 0.3203 \| 19.0 \| \| 55.6661 \| 5.12 \| 3300 \| 24.6176 \| 0.6319 \| 0.0 \| 0.6419 \| 0.6299 \| 19.0 \| \| 55.6661 \| 5.27 \| 3400 \| 23.6474 \| 1.6632 \| 0.0033 \| 1.665 \| 1.6244 \| 19.0 \| \| 45.1105 \| 5.43 \| 3500 \| 22.7063 \| 3.1374 \| 0.0 \| 3.1331 \| 3.1333 \| 19.0 \| \| 45.1105 \| 5.58 \| 3600 \| 21.9191 \| 5.0757 \| 0.0 \| 5.0694 \| 5.0456 \| 19.0 \| \| 45.1105 \| 5.74 \| 3700 \| 21.3359 \| 5.6576 \| 0.0 \| 5.689 \| 5.6772 \| 19.0 \| \| 45.1105 \| 5.89 \| 3800 \| 20.6990 \| 5.828 \| 0.0 \| 5.8801 \| 5.8688 \| 19.0 \| \| 45.1105 \| 6.05 \| 3900 \| 20.1800 \| 6.3727 \| 0.0 \| 6.3801 \| 6.3716 \| 19.0 \| \| 39.6923 \| 6.2 \| 4000 \| 19.7415 \| 6.2209 \| 0.0 \| 6.2347 \| 6.2368 \| 19.0 \| \| 39.6923 \| 6.36 \| 4100 \| 19.2800 \| 5.7215 \| 0.0 \| 5.7452 \| 5.7295 \| 19.0 \| \| 39.6923 \| 6.51 \| 4200 \| 18.9683 \| 6.1018 \| 0.0062 \| 6.1 \| 6.0935 \| 19.0 \| \| 39.6923 \| 6.67 \| 4300 \| 18.5776 \| 6.0354 \| 0.0062 \| 6.0227 \| 6.0103 \| 19.0 \| \| 39.6923 \| 6.82 \| 4400 \| 18.2629 \| 5.4438 \| 0.0062 \| 5.441 \| 5.4629 \| 19.0 \| \| 36.1688 \| 6.98 \| 4500 \| 18.0268 \| 5.3214 \| 0.0091 \| 5.3093 \| 5.2992 \| 19.0 \| \| 36.1688 \| 7.13 \| 4600 \| 17.7740 \| 5.2223 \| 0.0123 \| 5.2132 \| 5.2084 \| 19.0 \| \| 36.1688 \| 7.29 \| 4700 \| 17.5345 \| 5.178 \| 0.0231 \| 5.1615 \| 5.1243 \| 19.0 \| \| 36.1688 \| 7.44 \| 4800 \| 17.3846 \| 5.3899 \| 0.0277 \| 5.3414 \| 5.3534 \| 19.0 \| \| 36.1688 \| 7.6 \| 4900 \| 17.1999 \| 5.315 \| 0.0272 \| 5.2572 \| 5.2477 \| 19.0 \| \| 33.5745 \| 7.75 \| 5000 \| 17.0078 \| 5.9014 \| 0.028 \| 5.8181 \| 5.8058 \| 19.0 \| \| 33.5745 \| 7.91 \| 5100 \| 16.6418 \| 5.7546 \| 0.0242 \| 5.6903 \| 5.6746 \| 19.0 \| \| 33.5745 \| 8.06 \| 5200 \| 16.6330 \| 6.6893 \| 0.0182 \| 6.6354 \| 6.6178 \| 19.0 \| \| 33.5745 \| 8.22 \| 5300 \| 16.3423 \| 6.1679 \| 0.0072 \| 6.1518 \| 6.128 \| 19.0 \| \| 33.5745 \| 8.37 \| 5400 \| 16.2373 \| 6.7659 \| 0.0139 \| 6.7271 \| 6.7076 \| 19.0 \| \| 31.9486 \| 8.53 \| 5500 \| 16.1523 \| 7.1991 \| 0.0139 \| 7.1674 \| 7.1283 \| 19.0 \| \| 31.9486 \| 8.68 \| 5600 \| 16.0607 \| 7.7042 \| 0.0169 \| 7.6741 \| 7.6537 \| 19.0 \| \| 31.9486 \| 8.84 \| 5700 \| 15.7647 \| 7.1238 \| 0.02 \| 7.1113 \| 7.0586 \| 19.0 \| \| 31.9486 \| 8.99 \| 5800 \| 15.6194 \| 7.3055 \| 0.0116 \| 7.3311 \| 7.2683 \| 19.0 \| \| 31.9486 \| 9.15 \| 5900 \| 15.4994 \| 7.3365 \| 0.0139 \| 7.3026 \| 7.2708 \| 19.0 \| \| 30.5224 \| 9.3 \| 6000 \| 15.4207 \| 8.1959 \| 0.0116 \| 8.1917 \| 8.1651 \| 19.0 \| \| 30.5224 \| 9.46 \| 6100 \| 15.2981 \| 7.7936 \| 0.0144 \| 7.7826 \| 7.7488 \| 19.0 \| \| 30.5224 \| 9.61 \| 6200 \| 15.2391 \| 7.95 \| 0.0144 \| 7.9371 \| 7.895 \| 19.0 \| \| 30.5224 \| 9.77 \| 6300 \| 15.0941 \| 7.1669 \| 0.0144 \| 7.146 \| 7.1251 \| 19.0 \| \| 30.5224 \| 9.92 \| 6400 \| 14.9979 \| 6.2157 \| 0.0076 \| 6.2086 \| 6.1774 \| 19.0 \| \| 29.1236 \| 10.08 \| 6500 \| 14.9523 \| 7.4422 \| 0.0137 \| 7.3929 \| 7.393 \| 19.0 \| \| 29.1236 \| 10.23 \| 6600 \| 14.9515 \| 7.2375 \| 0.0137 \| 7.1728 \| 7.1779 \| 19.0 \| \| 29.1236 \| 10.39 \| 6700 \| 14.8874 \| 7.5071 \| 0.0068 \| 7.4544 \| 7.4739 \| 19.0 \| \| 29.1236 \| 10.54 \| 6800 \| 14.8057 \| 5.9608 \| 0.0169 \| 5.8754 \| 5.8691 \| 19.0 \| \| 29.1236 \| 10.7 \| 6900 \| 14.6818 \| 5.6345 \| 0.021 \| 5.5422 \| 5.5331 \| 19.0 \| \| 28.314 \| 10.85 \| 7000 \| 14.5409 \| 5.5799 \| 0.0169 \| 5.4915 \| 5.4833 \| 19.0 \| \| 28.314 \| 11.01 \| 7100 \| 14.4512 \| 4.3498 \| 0.0368 \| 4.2243 \| 4.2193 \| 19.0 \| \| 28.314 \| 11.16 \| 7200 \| 14.4560 \| 4.0453 \| 0.0372 \| 3.9481 \| 3.9228 \| 19.0 \| \| 28.314 \| 11.32 \| 7300 \| 14.3851 \| 5.1332 \| 0.0426 \| 5.0186 \| 4.9882 \| 19.0 \| \| 28.314 \| 11.47 \| 7400 \| 14.2265 \| 4.8944 \| 0.0371 \| 4.7869 \| 4.7765 \| 19.0 \| \| 27.5349 \| 11.63 \| 7500 \| 14.1214 \| 3.8846 \| 0.0335 \| 3.7882 \| 3.7677 \| 19.0 \| \| 27.5349 \| 11.78 \| 7600 \| 14.1505 \| 3.9992 \| 0.0514 \| 3.883 \| 3.8385 \| 19.0 \| \| 27.5349 \| 11.94 \| 7700 \| 13.9923 \| 3.4526 \| 0.0664 \| 3.325 \| 3.3258 \| 19.0 \| \| 27.5349 \| 12.09 \| 7800 \| 14.0299 \| 2.3086 \| 0.0346 \| 2.25 \| 2.219 \| 19.0 \| \| 27.5349 \| 12.25 \| 7900 \| 13.9814 \| 2.4402 \| 0.0628 \| 2.3282 \| 2.3004 \| 19.0 \| \| 26.4286 \| 12.4 \| 8000 \| 13.8561 \| 2.9869 \| 0.0654 \| 2.8769 \| 2.8485 \| 19.0 \| \| 26.4286 \| 12.56 \| 8100 \| 13.8259 \| 1.9609 \| 0.0386 \| 1.8863 \| 1.8846 \| 19.0 \| \| 26.4286 \| 12.71 \| 8200 \| 13.8127 \| 2.0628 \| 0.0355 \| 1.9915 \| 1.9738 \| 19.0 \| \| 26.4286 \| 12.87 \| 8300 \| 13.7174 \| 1.9904 \| 0.081 \| 1.888 \| 1.9069 \| 19.0 \| \| 26.4286 \| 13.02 \| 8400 \| 13.6308 \| 2.1398 \| 0.1055 \| 2.0204 \| 2.0468 \| 19.0 \| \| 26.108 \| 13.18 \| 8500 \| 13.6490 \| 1.8934 \| 0.0788 \| 1.7942 \| 1.8188 \| 19.0 \| \| 26.108 \| 13.33 \| 8600 \| 13.5996 \| 1.8746 \| 0.0901 \| 1.7441 \| 1.8006 \| 19.0 \| \| 26.108 \| 13.49 \| 8700 \| 13.5394 \| 1.7846 \| 0.0895 \| 1.6648 \| 1.7331 \| 19.0 \| \| 26.108 \| 13.64 \| 8800 \| 13.5368 \| 2.1345 \| 0.1287 \| 1.9808 \| 2.0814 \| 19.0 \| \| 26.108 \| 13.8 \| 8900 \| 13.4793 \| 2.5234 \| 0.1611 \| 2.3289 \| 2.4292 \| 19.0 \| \| 25.4931 \| 13.95 \| 9000 \| 13.3633 \| 2.8056 \| 0.1953 \| 2.5619 \| 2.7088 \| 19.0 \| \| 25.4931 \| 14.11 \| 9100 \| 13.5182 \| 3.087 \| 0.2192 \| 2.8182 \| 2.9928 \| 19.0 \| \| 25.4931 \| 14.26 \| 9200 \| 13.3372 \| 2.6353 \| 0.175 \| 2.4145 \| 2.589 \| 19.0 \| \| 25.4931 \| 14.42 \| 9300 \| 13.2822 \| 2.7577 \| 0.1905 \| 2.5277 \| 2.7215 \| 19.0 \| \| 25.4931 \| 14.57 \| 9400 \| 13.2011 \| 3.1891 \| 0.2381 \| 2.9276 \| 3.142 \| 19.0 \| \| 24.9241 \| 14.73 \| 9500 \| 13.2201 \| 2.609 \| 0.1683 \| 2.4162 \| 2.5905 \| 19.0 \| \| 24.9241 \| 14.88 \| 9600 \| 13.2206 \| 3.1083 \| 0.2241 \| 2.8627 \| 3.0606 \| 19.0 \| \| 24.9241 \| 15.04 \| 9700 \| 13.2157 \| 3.6233 \| 0.2731 \| 3.338 \| 3.5642 \| 19.0 \| \| 24.9241 \| 15.19 \| 9800 \| 13.1195 \| 3.1785 \| 0.2318 \| 2.9449 \| 3.1306 \| 19.0 \| \| 24.9241 \| 15.35 \| 9900 \| 13.0481 \| 3.0249 \| 0.2192 \| 2.7991 \| 2.9925 \| 19.0 \| \| 24.4511 \| 15.5 \| 10000 \| 13.0693 \| 3.1189 \| 0.2287 \| 2.8726 \| 3.0669 \| 19.0 \| \| 24.4511 \| 15.66 \| 10100 \| 12.9204 \| 2.6405 \| 0.1899 \| 2.4337 \| 2.61 \| 19.0 \| \| 24.4511 \| 15.81 \| 10200 \| 12.9200 \| 2.9037 \| 0.2148 \| 2.6775 \| 2.8683 \| 19.0 \| \| 24.4511 \| 15.97 \| 10300 \| 12.9203 \| 2.8847 \| 0.2034 \| 2.6586 \| 2.8438 \| 19.0 \| \| 24.4511 \| 16.12 \| 10400 \| 12.8723 \| 2.8195 \| 0.1976 \| 2.5922 \| 2.7803 \| 19.0 \| \| 23.8949 \| 16.28 \| 10500 \| 12.9749 \| 3.2658 \| 0.2217 \| 2.9905 \| 3.2262 \| 19.0 \| \| 23.8949 \| 16.43 \| 10600 \| 12.7975 \| 2.9762 \| 0.1844 \| 2.7295 \| 2.9474 \| 19.0 \| \| 23.8949 \| 16.59 \| 10700 \| 12.7497 \| 2.5496 \| 0.1406 \| 2.3536 \| 2.5269 \| 19.0 \| \| 23.8949 \| 16.74 \| 10800 \| 12.6485 \| 2.5509 \| 0.1454 \| 2.343 \| 2.5182 \| 19.0 \| \| 23.8949 \| 16.9 \| 10900 \| 12.6574 \| 2.1914 \| 0.1281 \| 2.0113 \| 2.1574 \| 19.0 \| \| 23.4963 \| 17.05 \| 11000 \| 12.6919 \| 2.1748 \| 0.1299 \| 1.9909 \| 2.1229 \| 19.0 \| \| 23.4963 \| 17.21 \| 11100 \| 12.5660 \| 2.3751 \| 0.1177 \| 2.1417 \| 2.326 \| 19.0 \| \| 23.4963 \| 17.36 \| 11200 \| 12.5866 \| 2.6893 \| 0.1344 \| 2.4378 \| 2.6318 \| 19.0 \| \| 23.4963 \| 17.52 \| 11300 \| 12.5427 \| 2.5546 \| 0.1411 \| 2.3175 \| 2.5073 \| 19.0 \| \| 23.4963 \| 17.67 \| 11400 \| 12.5011 \| 2.347 \| 0.1223 \| 2.1322 \| 2.3077 \| 19.0 \| \| 23.1492 \| 17.83 \| 11500 \| 12.5168 \| 2.2304 \| 0.1141 \| 2.0657 \| 2.1951 \| 19.0 \| \| 23.1492 \| 17.98 \| 11600 \| 12.4043 \| 2.4485 \| 0.1209 \| 2.2548 \| 2.4114 \| 19.0 \| \| 23.1492 \| 18.14 \| 11700 \| 12.4192 \| 2.0551 \| 0.0887 \| 1.8996 \| 2.0199 \| 19.0 \| \| 23.1492 \| 18.29 \| 11800 \| 12.3799 \| 2.1076 \| 0.0932 \| 1.9464 \| 2.0589 \| 19.0 \| \| 23.1492 \| 18.45 \| 11900 \| 12.4263 \| 2.4136 \| 0.1152 \| 2.2172 \| 2.357 \| 19.0 \| \| 22.7005 \| 18.6 \| 12000 \| 12.3218 \| 2.1197 \| 0.1105 \| 1.9997 \| 2.0873 \| 19.0 \| \| 22.7005 \| 18.76 \| 12100 \| 12.3297 \| 2.1883 \| 0.1102 \| 2.0414 \| 2.1267 \| 19.0 \| \| 22.7005 \| 18.91 \| 12200 \| 12.3026 \| 1.966 \| 0.0954 \| 1.8387 \| 1.9469 \| 19.0 \| \| 22.7005 \| 19.07 \| 12300 \| 12.3030 \| 2.0179 \| 0.0955 \| 1.8834 \| 1.9858 \| 19.0 \| \| 22.7005 \| 19.22 \| 12400 \| 12.2478 \| 1.9549 \| 0.0948 \| 1.8437 \| 1.9092 \| 19.0 \| \| 22.3178 \| 19.38 \| 12500 \| 12.1803 \| 1.6396 \| 0.0648 \| 1.5296 \| 1.6208 \| 19.0 \| \| 22.3178 \| 19.53 \| 12600 \| 12.1732 \| 1.5568 \| 0.0769 \| 1.4894 \| 1.5387 \| 19.0 \| \| 22.3178 \| 19.69 \| 12700 \| 12.1342 \| 1.6861 \| 0.0782 \| 1.6105 \| 1.666 \| 19.0 \| \| 22.3178 \| 19.84 \| 12800 \| 12.1313 \| 2.023 \| 0.0965 \| 1.9295 \| 2.0072 \| 19.0 \| \| 22.3178 \| 20.0 \| 12900 \| 12.1315 \| 1.5878 \| 0.0701 \| 1.5153 \| 1.5467 \| 19.0 \| \| 21.8344 \| 20.16 \| 13000 \| 12.0611 \| 1.6406 \| 0.0637 \| 1.5665 \| 1.6033 \| 19.0 \| \| 21.8344 \| 20.31 \| 13100 \| 12.0327 \| 1.5913 \| 0.0544 \| 1.5209 \| 1.552 \| 19.0 \| \| 21.8344 \| 20.47 \| 13200 \| 12.0466 \| 1.3618 \| 0.0494 \| 1.3186 \| 1.33 \| 19.0 \| \| 21.8344 \| 20.62 \| 13300 \| 12.0787 \| 1.4445 \| 0.0451 \| 1.4073 \| 1.41 \| 19.0 \| \| 21.8344 \| 20.78 \| 13400 \| 11.9829 \| 1.3465 \| 0.0494 \| 1.3247 \| 1.3167 \| 19.0 \| \| 21.6309 \| 20.93 \| 13500 \| 11.9072 \| 1.4165 \| 0.0519 \| 1.3761 \| 1.3839 \| 19.0 \| \| 21.6309 \| 21.09 \| 13600 \| 11.9261 \| 1.3969 \| 0.0502 \| 1.3606 \| 1.3618 \| 19.0 \| \| 21.6309 \| 21.24 \| 13700 \| 11.8313 \| 1.3337 \| 0.0337 \| 1.2974 \| 1.316 \| 19.0 \| \| 21.6309 \| 21.4 \| 13800 \| 11.7709 \| 1.3045 \| 0.0371 \| 1.2746 \| 1.2889 \| 19.0 \| \| 21.6309 \| 21.55 \| 13900 \| 11.8402 \| 1.6106 \| 0.0391 \| 1.5678 \| 1.5697 \| 19.0 \| \| 21.2262 \| 21.71 \| 14000 \| 11.7132 \| 1.3261 \| 0.0222 \| 1.296 \| 1.3051 \| 19.0 \| \| 21.2262 \| 21.86 \| 14100 \| 11.7206 \| 1.41 \| 0.0252 \| 1.374 \| 1.3985 \| 19.0 \| \| 21.2262 \| 22.02 \| 14200 \| 11.7033 \| 1.6231 \| 0.0478 \| 1.5632 \| 1.5851 \| 19.0 \| \| 21.2262 \| 22.17 \| 14300 \| 11.7385 \| 1.8974 \| 0.0618 \| 1.8339 \| 1.8583 \| 19.0 \| \| 21.2262 \| 22.33 \| 14400 \| 11.6519 \| 1.8998 \| 0.0541 \| 1.8285 \| 1.8552 \| 19.0 \| \| 20.8055 \| 22.48 \| 14500 \| 11.6039 \| 1.9561 \| 0.0582 \| 1.859 \| 1.9073 \| 19.0 \| \| 20.8055 \| 22.64 \| 14600 \| 11.6322 \| 1.7731 \| 0.0442 \| 1.7061 \| 1.7303 \| 19.0 \| \| 20.8055 \| 22.79 \| 14700 \| 11.6046 \| 1.8874 \| 0.0618 \| 1.8083 \| 1.8539 \| 19.0 \| \| 20.8055 \| 22.95 \| 14800 \| 11.5051 \| 1.4271 \| 0.016 \| 1.3996 \| 1.4086 \| 19.0 \| \| 20.8055 \| 23.1 \| 14900 \| 11.5564 \| 1.743 \| 0.0451 \| 1.6787 \| 1.727 \| 19.0 \| \| 20.6263 \| 23.26 \| 15000 \| 11.5024 \| 1.9313 \| 0.0575 \| 1.8357 \| 1.887 \| 19.0 \| \| 20.6263 \| 23.41 \| 15100 \| 11.5281 \| 2.082 \| 0.0435 \| 1.9865 \| 2.0327 \| 19.0 \| \| 20.6263 \| 23.57 \| 15200 \| 11.4223 \| 1.9773 \| 0.0332 \| 1.9038 \| 1.9432 \| 19.0 \| \| 20.6263 \| 23.72 \| 15300 \| 11.4675 \| 1.7845 \| 0.0831 \| 1.6835 \| 1.7414 \| 19.0 \| \| 20.6263 \| 23.88 \| 15400 \| 11.3882 \| 2.1183 \| 0.0715 \| 1.9965 \| 2.0725 \| 19.0 \| \| 20.3154 \| 24.03 \| 15500 \| 11.4197 \| 2.4045 \| 0.1336 \| 2.2302 \| 2.3024 \| 19.0 \| \| 20.3154 \| 24.19 \| 15600 \| 11.3558 \| 1.9596 \| 0.1196 \| 1.8152 \| 1.8748 \| 19.0 \| \| 20.3154 \| 24.34 \| 15700 \| 11.3438 \| 2.0931 \| 0.111 \| 1.9469 \| 1.999 \| 19.0 \| \| 20.3154 \| 24.5 \| 15800 \| 11.3021 \| 2.2159 \| 0.1257 \| 2.0511 \| 2.1345 \| 19.0 \| \| 20.3154 \| 24.65 \| 15900 \| 11.3178 \| 2.093 \| 0.132 \| 1.9083 \| 1.9969 \| 19.0 \| \| 20.0858 \| 24.81 \| 16000 \| 11.2377 \| 1.6589 \| 0.1129 \| 1.5625 \| 1.6245 \| 19.0 \| \| 20.0858 \| 24.96 \| 16100 \| 11.2058 \| 1.6667 \| 0.0854 \| 1.5597 \| 1.6223 \| 19.0 \| \| 20.0858 \| 25.12 \| 16200 \| 11.1602 \| 2.0907 \| 0.1219 \| 1.9297 \| 1.9988 \| 19.0 \| \| 20.0858 \| 25.27 \| 16300 \| 11.1666 \| 1.86 \| 0.1092 \| 1.7398 \| 1.7993 \| 19.0 \| \| 20.0858 \| 25.43 \| 16400 \| 11.1807 \| 1.8879 \| 0.1818 \| 1.7579 \| 1.8335 \| 19.0 \| \| 19.7588 \| 25.58 \| 16500 \| 11.1310 \| 2.0377 \| 0.1612 \| 1.8653 \| 1.9538 \| 19.0 \| \| 19.7588 \| 25.74 \| 16600 \| 11.1577 \| 2.1441 \| 0.1767 \| 1.9546 \| 2.0518 \| 19.0 \| \| 19.7588 \| 25.89 \| 16700 \| 11.0748 \| 1.8679 \| 0.1892 \| 1.7249 \| 1.7822 \| 19.0 \| \| 19.7588 \| 26.05 \| 16800 \| 11.1048 \| 2.2775 \| 0.2072 \| 2.0566 \| 2.1521 \| 19.0 \| \| 19.7588 \| 26.2 \| 16900 \| 11.0498 \| 1.8117 \| 0.161 \| 1.6879 \| 1.7357 \| 19.0 \| \| 19.4627 \| 26.36 \| 17000 \| 11.0435 \| 1.7875 \| 0.1627 \| 1.6626 \| 1.7306 \| 19.0 \| \| 19.4627 \| 26.51 \| 17100 \| 10.9406 \| 1.7333 \| 0.1645 \| 1.6051 \| 1.6671 \| 19.0 \| \| 19.4627 \| 26.67 \| 17200 \| 10.9242 \| 1.596 \| 0.1426 \| 1.4747 \| 1.5341 \| 19.0 \| \| 19.4627 \| 26.82 \| 17300 \| 10.9571 \| 1.9874 \| 0.2109 \| 1.8109 \| 1.9061 \| 19.0 \| \| 19.4627 \| 26.98 \| 17400 \| 10.9265 \| 1.6999 \| 0.1353 \| 1.5574 \| 1.6402 \| 19.0 \| \| 19.2619 \| 27.13 \| 17500 \| 10.8919 \| 1.7543 \| 0.1709 \| 1.587 \| 1.6605 \| 19.0 \| \| 19.2619 \| 27.29 \| 17600 \| 10.8382 \| 2.126 \| 0.2056 \| 1.8609 \| 2.0021 \| 19.0 \| \| 19.2619 \| 27.44 \| 17700 \| 10.8936 \| 1.9626 \| 0.1726 \| 1.7402 \| 1.8665 \| 19.0 \| \| 19.2619 \| 27.6 \| 17800 \| 10.8565 \| 1.7668 \| 0.1673 \| 1.5914 \| 1.7099 \| 19.0 \| \| 19.2619 \| 27.75 \| 17900 \| 10.9047 \| 2.0972 \| 0.1867 \| 1.8519 \| 2.0224 \| 19.0 \| \| 19.0457 \| 27.91 \| 18000 \| 10.7900 \| 2.7761 \| 0.2904 \| 2.4403 \| 2.6936 \| 19.0 \| \| 19.0457 \| 28.06 \| 18100 \| 10.7191 \| 2.3652 \| 0.2431 \| 2.0989 \| 2.2767 \| 19.0 \| \| 19.0457 \| 28.22 \| 18200 \| 10.7462 \| 3.3125 \| 0.361 \| 2.847 \| 3.1506 \| 19.0 \| \| 19.0457 \| 28.37 \| 18300 \| 10.7721 \| 2.9247 \| 0.3 \| 2.5443 \| 2.806 \| 19.0 \| \| 19.0457 \| 28.53 \| 18400 \| 10.7208 \| 2.5398 \| 0.2812 \| 2.2211 \| 2.4312 \| 19.0 \| \| 18.8301 \| 28.68 \| 18500 \| 10.6708 \| 2.5902 \| 0.281 \| 2.2765 \| 2.4881 \| 19.0 \| \| 18.8301 \| 28.84 \| 18600 \| 10.7220 \| 2.276 \| 0.2061 \| 1.9904 \| 2.1922 \| 19.0 \| \| 18.8301 \| 28.99 \| 18700 \| 10.6855 \| 2.8678 \| 0.3496 \| 2.52 \| 2.751 \| 19.0 \| \| 18.8301 \| 29.15 \| 18800 \| 10.6550 \| 2.5232 \| 0.2724 \| 2.2108 \| 2.4314 \| 19.0 \| \| 18.8301 \| 29.3 \| 18900 \| 10.6488 \| 2.5629 \| 0.2203 \| 2.2361 \| 2.4261 \| 19.0 \| \| 18.5872 \| 29.46 \| 19000 \| 10.6123 \| 2.5052 \| 0.1923 \| 2.1381 \| 2.3821 \| 19.0 \| \| 18.5872 \| 29.61 \| 19100 \| 10.6105 \| 3.7779 \| 0.3653 \| 3.2404 \| 3.5759 \| 19.0 \| \| 18.5872 \| 29.77 \| 19200 \| 10.5823 \| 3.8282 \| 0.3743 \| 3.2645 \| 3.6077 \| 19.0 \| \| 18.5872 \| 29.92 \| 19300 \| 10.5606 \| 3.0976 \| 0.277 \| 2.6041 \| 2.8838 \| 19.0 \| \| 18.5872 \| 30.08 \| 19400 \| 10.5846 \| 3.638 \| 0.3482 \| 3.0804 \| 3.4294 \| 19.0 \| \| 18.2839 \| 30.23 \| 19500 \| 10.4722 \| 2.6173 \| 0.2326 \| 2.2268 \| 2.4656 \| 19.0 \| \| 18.2839 \| 30.39 \| 19600 \| 10.5211 \| 3.5085 \| 0.3377 \| 2.9751 \| 3.2889 \| 19.0 \| \| 18.2839 \| 30.54 \| 19700 \| 10.4735 \| 2.4781 \| 0.2097 \| 2.1099 \| 2.3338 \| 19.0 \| \| 18.2839 \| 30.7 \| 19800 \| 10.4545 \| 3.1459 \| 0.3022 \| 2.6844 \| 2.9559 \| 19.0 \| \| 18.2839 \| 30.85 \| 19900 \| 10.4525 \| 3.6095 \| 0.3637 \| 3.0873 \| 3.3886 \| 19.0 \| \| 18.1352 \| 31.01 \| 20000 \| 10.4409 \| 4.0556 \| 0.4621 \| 3.3857 \| 3.7778 \| 19.0 \| \| 18.1352 \| 31.16 \| 20100 \| 10.4132 \| 3.8346 \| 0.3863 \| 3.2323 \| 3.6266 \| 19.0 \| \| 18.1352 \| 31.32 \| 20200 \| 10.4468 \| 2.3736 \| 0.1977 \| 2.0195 \| 2.236 \| 19.0 \| \| 18.1352 \| 31.47 \| 20300 \| 10.3896 \| 3.6954 \| 0.3512 \| 3.1402 \| 3.4667 \| 19.0 \| \| 18.1352 \| 31.63 \| 20400 \| 10.3546 \| 3.5158 \| 0.3558 \| 3.0575 \| 3.3116 \| 19.0 \| \| 17.9834 \| 31.78 \| 20500 \| 10.3632 \| 3.179 \| 0.3374 \| 2.7634 \| 2.9846 \| 19.0 \| \| 17.9834 \| 31.94 \| 20600 \| 10.3168 \| 3.9121 \| 0.4012 \| 3.3812 \| 3.687 \| 19.0 \| \| 17.9834 \| 32.09 \| 20700 \| 10.2772 \| 3.6148 \| 0.3667 \| 3.1059 \| 3.3541 \| 19.0 \| \| 17.9834 \| 32.25 \| 20800 \| 10.3173 \| 3.1448 \| 0.2924 \| 2.6948 \| 2.9338 \| 19.0 \| \| 17.9834 \| 32.4 \| 20900 \| 10.2154 \| 2.4611 \| 0.1922 \| 2.1597 \| 2.3288 \| 19.0 \| \| 17.6192 \| 32.56 \| 21000 \| 10.2957 \| 3.3177 \| 0.3762 \| 2.8085 \| 3.0595 \| 19.0 \| \| 17.6192 \| 32.71 \| 21100 \| 10.2064 \| 3.4663 \| 0.3819 \| 3.0229 \| 3.2201 \| 19.0 \| \| 17.6192 \| 32.87 \| 21200 \| 10.2235 \| 3.245 \| 0.3179 \| 2.7618 \| 3.0066 \| 19.0 \| \| 17.6192 \| 33.02 \| 21300 \| 10.2193 \| 2.5572 \| 0.2775 \| 2.216 \| 2.3892 \| 19.0 \| \| 17.6192 \| 33.18 \| 21400 \| 10.2467 \| 3.4873 \| 0.3934 \| 3.02 \| 3.2701 \| 19.0 \| \| 17.5532 \| 33.33 \| 21500 \| 10.2378 \| 2.8087 \| 0.3049 \| 2.4001 \| 2.6218 \| 19.0 \| \| 17.5532 \| 33.49 \| 21600 \| 10.2086 \| 3.8967 \| 0.4801 \| 3.3678 \| 3.603 \| 19.0 \| \| 17.5532 \| 33.64 \| 21700 \| 10.2384 \| 2.6534 \| 0.3239 \| 2.3276 \| 2.4692 \| 19.0 \| \| 17.5532 \| 33.8 \| 21800 \| 10.1929 \| 2.6025 \| 0.2845 \| 2.2653 \| 2.4507 \| 19.0 \| \| 17.5532 \| 33.95 \| 21900 \| 10.1016 \| 3.3244 \| 0.377 \| 2.8311 \| 3.0784 \| 19.0 \| \| 17.3872 \| 34.11 \| 22000 \| 10.1407 \| 3.4245 \| 0.4024 \| 3.044 \| 3.1865 \| 19.0 \| \| 17.3872 \| 34.26 \| 22100 \| 10.0760 \| 3.9251 \| 0.4272 \| 3.4064 \| 3.6497 \| 19.0 \| \| 17.3872 \| 34.42 \| 22200 \| 10.0998 \| 3.3034 \| 0.3438 \| 2.8977 \| 3.1141 \| 19.0 \| \| 17.3872 \| 34.57 \| 22300 \| 10.0834 \| 2.4967 \| 0.266 \| 2.2301 \| 2.3647 \| 19.0 \| \| 17.3872 \| 34.73 \| 22400 \| 9.9902 \| 4.0828 \| 0.4867 \| 3.5482 \| 3.7861 \| 19.0 \| \| 17.1744 \| 34.88 \| 22500 \| 10.0366 \| 3.5772 \| 0.4377 \| 3.1153 \| 3.3199 \| 19.0 \| \| 17.1744 \| 35.04 \| 22600 \| 10.0299 \| 3.5342 \| 0.433 \| 3.0501 \| 3.2176 \| 19.0 \| \| 17.1744 \| 35.19 \| 22700 \| 9.9912 \| 3.7754 \| 0.4445 \| 3.3191 \| 3.502 \| 19.0 \| \| 17.1744 \| 35.35 \| 22800 \| 9.9580 \| 4.5086 \| 0.5514 \| 3.8986 \| 4.1987 \| 19.0 \| \| 17.1744 \| 35.5 \| 22900 \| 9.9676 \| 3.526 \| 0.3942 \| 3.0859 \| 3.3082 \| 19.0 \| \| 17.0687 \| 35.66 \| 23000 \| 9.9874 \| 3.7058 \| 0.5139 \| 3.2353 \| 3.4611 \| 19.0 \| \| 17.0687 \| 35.81 \| 23100 \| 9.9536 \| 3.6588 \| 0.4552 \| 3.1591 \| 3.3554 \| 19.0 \| \| 17.0687 \| 35.97 \| 23200 \| 9.8948 \| 3.6279 \| 0.3933 \| 3.1403 \| 3.3426 \| 19.0 \| \| 17.0687 \| 36.12 \| 23300 \| 9.8397 \| 3.8101 \| 0.4971 \| 3.3152 \| 3.5133 \| 19.0 \| \| 17.0687 \| 36.28 \| 23400 \| 9.8995 \| 3.3201 \| 0.4209 \| 2.9101 \| 3.0903 \| 19.0 \| \| 16.7686 \| 36.43 \| 23500 \| 9.9085 \| 4.0108 \| 0.6389 \| 3.5055 \| 3.7286 \| 19.0 \| \| 16.7686 \| 36.59 \| 23600 \| 9.8688 \| 3.6051 \| 0.5164 \| 3.1651 \| 3.3781 \| 19.0 \| \| 16.7686 \| 36.74 \| 23700 \| 9.8673 \| 4.4987 \| 0.6051 \| 3.8789 \| 4.1868 \| 19.0 \| \| 16.7686 \| 36.9 \| 23800 \| 9.8848 \| 3.6926 \| 0.5635 \| 3.1681 \| 3.3902 \| 19.0 \| \| 16.7686 \| 37.05 \| 23900 \| 9.8497 \| 3.518 \| 0.4283 \| 3.1159 \| 3.3112 \| 19.0 \| \| 16.7432 \| 37.21 \| 24000 \| 9.8044 \| 3.3369 \| 0.3772 \| 2.9784 \| 3.147 \| 19.0 \| \| 16.7432 \| 37.36 \| 24100 \| 9.7768 \| 3.5862 \| 0.3819 \| 3.1273 \| 3.3535 \| 19.0 \| \| 16.7432 \| 37.52 \| 24200 \| 9.7536 \| 4.1823 \| 0.5884 \| 3.645 \| 3.8843 \| 19.0 \| \| 16.7432 \| 37.67 \| 24300 \| 9.7953 \| 4.3981 \| 0.6441 \| 3.7941 \| 4.0623 \| 19.0 \| \| 16.7432 \| 37.83 \| 24400 \| 9.6742 \| 3.7833 \| 0.4755 \| 3.3516 \| 3.5543 \| 19.0 \| \| 16.5714 \| 37.98 \| 24500 \| 9.7946 \| 3.3839 \| 0.495 \| 3.0021 \| 3.156 \| 19.0 \| \| 16.5714 \| 38.14 \| 24600 \| 9.7544 \| 4.3873 \| 0.6486 \| 3.8188 \| 4.0653 \| 19.0 \| \| 16.5714 \| 38.29 \| 24700 \| 9.7586 \| 3.4403 \| 0.4756 \| 3.0402 \| 3.2405 \| 19.0 \| \| 16.5714 \| 38.45 \| 24800 \| 9.7895 \| 3.6822 \| 0.6247 \| 3.2612 \| 3.4746 \| 19.0 \| \| 16.5714 \| 38.6 \| 24900 \| 9.6964 \| 3.8743 \| 0.6209 \| 3.4159 \| 3.6051 \| 19.0 \| \| 16.3393 \| 38.76 \| 25000 \| 9.7190 \| 4.1508 \| 0.635 \| 3.5925 \| 3.8753 \| 19.0 \| \| 16.3393 \| 38.91 \| 25100 \| 9.6435 \| 3.6755 \| 0.4777 \| 3.268 \| 3.4572 \| 19.0 \| \| 16.3393 \| 39.07 \| 25200 \| 9.6390 \| 2.9478 \| 0.4049 \| 2.6531 \| 2.7782 \| 19.0 \| \| 16.3393 \| 39.22 \| 25300 \| 9.6300 \| 2.9973 \| 0.3897 \| 2.6662 \| 2.7943 \| 19.0 \| \| 16.3393 \| 39.38 \| 25400 \| 9.6229 \| 3.6726 \| 0.4182 \| 3.2207 \| 3.4595 \| 19.0 \| \| 16.3076 \| 39.53 \| 25500 \| 9.6392 \| 2.9691 \| 0.3692 \| 2.6709 \| 2.8182 \| 19.0 \| \| 16.3076 \| 39.69 \| 25600 \| 9.5978 \| 2.8167 \| 0.3437 \| 2.593 \| 2.7155 \| 19.0 \| \| 16.3076 \| 39.84 \| 25700 \| 9.6111 \| 3.5135 \| 0.5453 \| 3.1415 \| 3.3042 \| 19.0 \| \| 16.3076 \| 40.0 \| 25800 \| 9.6118 \| 3.459 \| 0.4963 \| 3.1351 \| 3.2809 \| 19.0 \| \| 16.3076 \| 40.16 \| 25900 \| 9.5994 \| 3.5735 \| 0.539 \| 3.2556 \| 3.3904 \| 19.0 \| \| 16.0684 \| 40.31 \| 26000 \| 9.5526 \| 3.3388 \| 0.4689 \| 2.9753 \| 3.1562 \| 19.0 \| \| 16.0684 \| 40.47 \| 26100 \| 9.5365 \| 3.0882 \| 0.392 \| 2.8072 \| 2.9556 \| 19.0 \| \| 16.0684 \| 40.62 \| 26200 \| 9.5571 \| 3.0022 \| 0.4109 \| 2.7108 \| 2.8575 \| 19.0 \| \| 16.0684 \| 40.78 \| 26300 \| 9.5240 \| 3.506 \| 0.5734 \| 3.1577 \| 3.3378 \| 19.0 \| \| 16.0684 \| 40.93 \| 26400 \| 9.4913 \| 3.5936 \| 0.5165 \| 3.2452 \| 3.4134 \| 19.0 \| \| 15.9425 \| 41.09 \| 26500 \| 9.5297 \| 3.7802 \| 0.6862 \| 3.4061 \| 3.5436 \| 19.0 \| \| 15.9425 \| 41.24 \| 26600 \| 9.4657 \| 3.8433 \| 0.6105 \| 3.4621 \| 3.638 \| 19.0 \| \| 15.9425 \| 41.4 \| 26700 \| 9.5049 \| 3.5822 \| 0.6462 \| 3.231 \| 3.3745 \| 19.0 \| \| 15.9425 \| 41.55 \| 26800 \| 9.4739 \| 2.9668 \| 0.4426 \| 2.7345 \| 2.8134 \| 19.0 \| \| 15.9425 \| 41.71 \| 26900 \| 9.4868 \| 3.7458 \| 0.6934 \| 3.3708 \| 3.5492 \| 19.0 \| \| 15.7779 \| 41.86 \| 27000 \| 9.4683 \| 3.5254 \| 0.6006 \| 3.1629 \| 3.3011 \| 19.0 \| \| 15.7779 \| 42.02 \| 27100 \| 9.4108 \| 4.2731 \| 0.7412 \| 3.8236 \| 4.0171 \| 19.0 \| \| 15.7779 \| 42.17 \| 27200 \| 9.3994 \| 3.5014 \| 0.5738 \| 3.1525 \| 3.3306 \| 19.0 \| \| 15.7779 \| 42.33 \| 27300 \| 9.3760 \| 3.4929 \| 0.4954 \| 3.1402 \| 3.3028 \| 19.0 \| \| 15.7779 \| 42.48 \| 27400 \| 9.4201 \| 4.2777 \| 0.7152 \| 3.7943 \| 4.0349 \| 19.0 \| \| 15.7238 \| 42.64 \| 27500 \| 9.3913 \| 3.6489 \| 0.6371 \| 3.2903 \| 3.4528 \| 19.0 \| \| 15.7238 \| 42.79 \| 27600 \| 9.4269 \| 3.5269 \| 0.6042 \| 3.2049 \| 3.3528 \| 19.0 \| \| 15.7238 \| 42.95 \| 27700 \| 9.3847 \| 3.4735 \| 0.5963 \| 3.1522 \| 3.2796 \| 19.0 \| \| 15.7238 \| 43.1 \| 27800 \| 9.3474 \| 3.8327 \| 0.6428 \| 3.406 \| 3.5698 \| 19.0 \| \| 15.7238 \| 43.26 \| 27900 \| 9.3293 \| 3.5475 \| 0.6313 \| 3.1725 \| 3.3367 \| 19.0 \| \| 15.5108 \| 43.41 \| 28000 \| 9.3802 \| 4.249 \| 0.7997 \| 3.7924 \| 3.9849 \| 19.0 \| \| 15.5108 \| 43.57 \| 28100 \| 9.2588 \| 3.4476 \| 0.4676 \| 3.1758 \| 3.2993 \| 19.0 \| \| 15.5108 \| 43.72 \| 28200 \| 9.3447 \| 4.0267 \| 0.7081 \| 3.6208 \| 3.7957 \| 19.0 \| \| 15.5108 \| 43.88 \| 28300 \| 9.2853 \| 4.0105 \| 0.7799 \| 3.5848 \| 3.7619 \| 19.0 \| \| 15.5108 \| 44.03 \| 28400 \| 9.2753 \| 3.1833 \| 0.4678 \| 2.9068 \| 3.0168 \| 19.0 \| \| 15.4004 \| 44.19 \| 28500 \| 9.2345 \| 3.6778 \| 0.5955 \| 3.3212 \| 3.4724 \| 19.0 \| \| 15.4004 \| 44.34 \| 28600 \| 9.3130 \| 3.9958 \| 0.6892 \| 3.5871 \| 3.772 \| 19.0 \| \| 15.4004 \| 44.5 \| 28700 \| 9.2984 \| 4.1868 \| 0.696 \| 3.7194 \| 3.9197 \| 19.0 \| \| 15.4004 \| 44.65 \| 28800 \| 9.2722 \| 3.8848 \| 0.5914 \| 3.5038 \| 3.7022 \| 19.0 \| ### Framework versions - Transformers 4.20.1 - Pytorch 1.12.0 - Datasets 2.3.2 - Tokenizers 0.12.1
jonatasgrosman/exp_w2v2t_it_wav2vec2_s211	jonatasgrosman	2022-07-08T18:47:36Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T18:46:52Z	--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_wav2vec2_s211 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_wav2vec2_s692	jonatasgrosman	2022-07-08T18:40:27Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T18:39:44Z	--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_wav2vec2_s692 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_vp-it_s621	jonatasgrosman	2022-07-08T18:34:01Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T18:33:37Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-it_s621 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_vp-it_s73	jonatasgrosman	2022-07-08T18:24:40Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T18:24:16Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-it_s73 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_r-wav2vec2_s303	jonatasgrosman	2022-07-08T18:20:50Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T18:20:08Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_r-wav2vec2_s303 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_r-wav2vec2_s201	jonatasgrosman	2022-07-08T18:16:03Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T18:15:40Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_r-wav2vec2_s201 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_r-wav2vec2_s911	jonatasgrosman	2022-07-08T18:12:55Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T18:12:33Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_r-wav2vec2_s911 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_xls-r_s42	jonatasgrosman	2022-07-08T18:06:10Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T18:05:28Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_xls-r_s42 Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_unispeech-sat_s635	jonatasgrosman	2022-07-08T17:58:13Z	4	0	transformers	[ "transformers", "pytorch", "unispeech-sat", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T17:57:49Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech-sat_s635 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
ndhieunguyen/ppo-SpaceInvadersNoFrameskip-v4	ndhieunguyen	2022-07-08T17:57:39Z	1	0	stable-baselines3	[ "stable-baselines3", "SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]	reinforcement-learning	2023-04-26T15:34:31Z	--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - metrics: - type: mean_reward value: 688.00 +/- 388.59 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 type: SpaceInvadersNoFrameskip-v4 --- # DQN Agent playing SpaceInvadersNoFrameskip-v4 This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4 using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/> SB3: https://github.com/DLR-RM/stable-baselines3<br/> SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib ``` # Download model and save it into the logs/ folder python -m utils.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga infinitejoy -f logs/ python enjoy.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` ## Training (with the RL Zoo) ``` python train.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ # Upload the model and generate video (when possible) python -m utils.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga infinitejoy ``` ## Hyperparameters ```python OrderedDict([('batch_size', 32), ('buffer_size', 100000), ('env_wrapper', ['stable_baselines3.common.atari_wrappers.AtariWrapper']), ('exploration_final_eps', 0.01), ('exploration_fraction', 0.1), ('frame_stack', 4), ('gradient_steps', 1), ('learning_rate', 0.0001), ('learning_starts', 100000), ('n_timesteps', 10000000.0), ('optimize_memory_usage', True), ('policy', 'CnnPolicy'), ('target_update_interval', 1000), ('train_freq', 4), ('normalize', False)]) ```
jonatasgrosman/exp_w2v2t_ja_unispeech-sat_s884	jonatasgrosman	2022-07-08T17:51:35Z	5	0	transformers	[ "transformers", "pytorch", "unispeech-sat", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T17:51:10Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech-sat_s884 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_vp-nl_s770	jonatasgrosman	2022-07-08T17:48:07Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T17:47:43Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-nl_s770 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_vp-nl_s287	jonatasgrosman	2022-07-08T17:44:15Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T17:43:51Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-nl_s287 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_vp-nl_s682	jonatasgrosman	2022-07-08T17:41:08Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T17:40:45Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-nl_s682 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_vp-es_s673	jonatasgrosman	2022-07-08T17:33:40Z	7	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T17:33:01Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-es_s673 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_vp-fr_s543	jonatasgrosman	2022-07-08T17:26:45Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T17:26:03Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-fr_s543 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_vp-fr_s458	jonatasgrosman	2022-07-08T17:22:44Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T17:22:19Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-fr_s458 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_vp-fr_s368	jonatasgrosman	2022-07-08T17:18:18Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T17:17:49Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-fr_s368 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
infinitejoy/dqn-SpaceInvadersNoFrameskip-v4	infinitejoy	2022-07-08T17:14:02Z	3	0	stable-baselines3	[ "stable-baselines3", "SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]	reinforcement-learning	2022-07-08T17:05:23Z	--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - metrics: - type: mean_reward value: 688.00 +/- 388.59 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 type: SpaceInvadersNoFrameskip-v4 --- # DQN Agent playing SpaceInvadersNoFrameskip-v4 This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4 using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/> SB3: https://github.com/DLR-RM/stable-baselines3<br/> SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib ``` # Download model and save it into the logs/ folder python -m utils.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga infinitejoy -f logs/ python enjoy.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` ## Training (with the RL Zoo) ``` python train.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ # Upload the model and generate video (when possible) python -m utils.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga infinitejoy ``` ## Hyperparameters ```python OrderedDict([('batch_size', 32), ('buffer_size', 100000), ('env_wrapper', ['stable_baselines3.common.atari_wrappers.AtariWrapper']), ('exploration_final_eps', 0.01), ('exploration_fraction', 0.1), ('frame_stack', 4), ('gradient_steps', 1), ('learning_rate', 0.0001), ('learning_starts', 100000), ('n_timesteps', 10000000.0), ('optimize_memory_usage', True), ('policy', 'CnnPolicy'), ('target_update_interval', 1000), ('train_freq', 4), ('normalize', False)]) ```
jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s886	jonatasgrosman	2022-07-08T17:06:46Z	5	0	transformers	[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T17:06:23Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech-ml_s886 Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_wavlm_s664	jonatasgrosman	2022-07-08T17:03:01Z	6	1	transformers	[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T17:02:32Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_wavlm_s664 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_vp-sv_s570	jonatasgrosman	2022-07-08T16:43:15Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T16:42:50Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-sv_s570 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
Nitika/distilbert-base-uncased-finetuned-squad-d5716d28	Nitika	2022-07-08T16:36:38Z	0	0	null	[ "pytorch", "question-answering", "en", "dataset:squad", "arxiv:1910.01108", "license:apache-2.0", "region:us" ]	question-answering	2022-07-08T16:36:27Z	--- language: - en thumbnail: https://github.com/karanchahal/distiller/blob/master/distiller.jpg tags: - question-answering license: apache-2.0 datasets: - squad metrics: - squad --- # DistilBERT with a second step of distillation ## Model description This model replicates the "DistilBERT (D)" model from Table 2 of the [DistilBERT paper](https://arxiv.org/pdf/1910.01108.pdf). In this approach, a DistilBERT student is fine-tuned on SQuAD v1.1, but with a BERT model (also fine-tuned on SQuAD v1.1) acting as a teacher for a second step of task-specific distillation. In this version, the following pre-trained models were used: * Student: `distilbert-base-uncased` * Teacher: `lewtun/bert-base-uncased-finetuned-squad-v1` ## Training data This model was trained on the SQuAD v1.1 dataset which can be obtained from the `datasets` library as follows: ```python from datasets import load_dataset squad = load_dataset('squad') ``` ## Training procedure ## Eval results \| \| Exact Match \| F1 \| \|------------------\|-------------\|------\| \| DistilBERT paper \| 79.1 \| 86.9 \| \| Ours \| 78.4 \| 86.5 \| The scores were calculated using the `squad` metric from `datasets`. ### BibTeX entry and citation info ```bibtex @misc{sanh2020distilbert, title={DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter}, author={Victor Sanh and Lysandre Debut and Julien Chaumond and Thomas Wolf}, year={2020}, eprint={1910.01108}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```
jonatasgrosman/exp_w2v2t_ja_hubert_s732	jonatasgrosman	2022-07-08T16:24:39Z	4	0	transformers	[ "transformers", "pytorch", "hubert", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T16:24:16Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_hubert_s732 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_unispeech_s947	jonatasgrosman	2022-07-08T16:21:33Z	4	0	transformers	[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T16:21:10Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech_s947 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_unispeech_s253	jonatasgrosman	2022-07-08T16:18:02Z	4	0	transformers	[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T16:17:38Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech_s253 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_unispeech_s569	jonatasgrosman	2022-07-08T16:14:48Z	3	0	transformers	[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T16:14:24Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech_s569 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_xlsr-53_s781	jonatasgrosman	2022-07-08T16:08:42Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T16:08:19Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_xlsr-53_s781 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_wav2vec2_s727	jonatasgrosman	2022-07-08T15:53:02Z	5	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T15:52:34Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_wav2vec2_s727 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_wav2vec2_s895	jonatasgrosman	2022-07-08T15:49:30Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T15:49:04Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_wav2vec2_s895 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_ja_wav2vec2_s834	jonatasgrosman	2022-07-08T15:46:20Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T15:45:39Z	--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_wav2vec2_s834 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
Rocketknight1/bert-dummy-seq	Rocketknight1	2022-07-08T15:45:02Z	3	0	transformers	[ "transformers", "tf", "bert", "text-classification", "generated_from_keras_callback", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2022-07-08T15:18:33Z	--- license: apache-2.0 tags: - generated_from_keras_callback model-index: - name: bert-dummy-seq results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # bert-dummy-seq This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. It achieves the following results on the evaluation set: ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: None - training_precision: float32 ### Training results ### Framework versions - Transformers 4.21.0.dev0 - TensorFlow 2.9.1 - Datasets 2.3.3.dev0 - Tokenizers 0.11.0
jonatasgrosman/exp_w2v2t_th_vp-it_s819	jonatasgrosman	2022-07-08T15:31:43Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T15:31:17Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-it_s819 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_vp-it_s259	jonatasgrosman	2022-07-08T15:28:35Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T15:28:09Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-it_s259 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
tfshaman/distilbert-base-uncased-distilled-clinc	tfshaman	2022-07-08T15:19:17Z	10	0	transformers	[ "transformers", "pytorch", "distilbert", "text-classification", "generated_from_trainer", "dataset:clinc_oos", "license:apache-2.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2022-07-08T14:52:51Z	--- license: apache-2.0 tags: - generated_from_trainer datasets: - clinc_oos metrics: - accuracy model-index: - name: distilbert-base-uncased-distilled-clinc results: - task: name: Text Classification type: text-classification dataset: name: clinc_oos type: clinc_oos args: plus metrics: - name: Accuracy type: accuracy value: 0.8264516129032258 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # distilbert-base-uncased-distilled-clinc This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset. It achieves the following results on the evaluation set: - Loss: 1.5565 - Accuracy: 0.8265 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| 3.2743 \| 1.0 \| 318 \| 2.5809 \| 0.7310 \| \| 2.2148 \| 2.0 \| 636 \| 1.7909 \| 0.8071 \| \| 1.7065 \| 3.0 \| 954 \| 1.5565 \| 0.8265 \| ### Framework versions - Transformers 4.21.0.dev0 - Pytorch 1.12.0 - Datasets 2.3.2 - Tokenizers 0.12.1
jonatasgrosman/exp_w2v2t_th_r-wav2vec2_s805	jonatasgrosman	2022-07-08T15:18:14Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T15:17:48Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_r-wav2vec2_s805 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_xls-r_s590	jonatasgrosman	2022-07-08T15:14:52Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T15:14:26Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_xls-r_s590 Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_xls-r_s879	jonatasgrosman	2022-07-08T15:11:46Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T15:11:20Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_xls-r_s879 Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_xls-r_s625	jonatasgrosman	2022-07-08T15:07:51Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T15:07:26Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_xls-r_s625 Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
dminiotas05/distilbert-base-uncased-finetuned-ft650_10class	dminiotas05	2022-07-08T14:58:07Z	5	0	transformers	[ "transformers", "pytorch", "tensorboard", "distilbert", "text-classification", "generated_from_trainer", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2022-07-08T14:33:27Z	--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-ft650_10class results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # distilbert-base-uncased-finetuned-ft650_10class This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.9674 - Accuracy: 0.2207 - F1: 0.2002 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| F1 \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\|:------:\| \| 2.1088 \| 1.0 \| 188 \| 2.0460 \| 0.1807 \| 0.1324 \| \| 1.9628 \| 2.0 \| 376 \| 1.9867 \| 0.2173 \| 0.1821 \| \| 1.8966 \| 3.0 \| 564 \| 1.9693 \| 0.2193 \| 0.1936 \| \| 1.8399 \| 4.0 \| 752 \| 1.9674 \| 0.2207 \| 0.2002 \| ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1
jonatasgrosman/exp_w2v2t_th_unispeech-sat_s658	jonatasgrosman	2022-07-08T14:57:17Z	4	0	transformers	[ "transformers", "pytorch", "unispeech-sat", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T14:56:29Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_unispeech-sat_s658 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_vp-nl_s947	jonatasgrosman	2022-07-08T14:53:03Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T14:52:36Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-nl_s947 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
micheljperez/dqn-SpaceInvadersNoFrameskip-v4-2	micheljperez	2022-07-08T14:47:15Z	2	0	stable-baselines3	[ "stable-baselines3", "SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]	reinforcement-learning	2022-07-05T13:17:28Z	--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - metrics: - type: mean_reward value: 1092.00 +/- 250.80 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 type: SpaceInvadersNoFrameskip-v4 --- # DQN Agent playing SpaceInvadersNoFrameskip-v4 This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4 using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/> SB3: https://github.com/DLR-RM/stable-baselines3<br/> SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib ``` # Download model and save it into the logs/ folder python -m utils.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga micheljperez -f logs/ python enjoy.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` ## Training (with the RL Zoo) ``` python train.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ # Upload the model and generate video (when possible) python -m utils.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga micheljperez ``` ## Hyperparameters ```python OrderedDict([('batch_size', 32), ('buffer_size', 100000), ('env_wrapper', ['stable_baselines3.common.atari_wrappers.AtariWrapper']), ('exploration_final_eps', 0.01), ('exploration_fraction', 0.07817), ('frame_stack', 4), ('gradient_steps', 1), ('learning_rate', 0.3571), ('learning_starts', 100000), ('n_timesteps', 10000000), ('optimize_memory_usage', True), ('policy', 'CnnPolicy'), ('target_update_interval', 1000), ('train_freq', 4), ('normalize', False)]) ```
Zengwei/icefall-asr-librispeech-conv-emformer-transducer-stateless2-larger-latency-2022-07-06	Zengwei	2022-07-08T14:40:32Z	0	0	null	[ "tensorboard", "region:us" ]	null	2022-07-06T08:44:45Z	# Introduction See https://github.com/k2-fsa/icefall/pull/440 This model use the following setup: * length of chunk is 64 frames (i.e., 0.64s) * length of right context is 16 frames (i.e., 0.16s)
Nonzerophilip/bert-finetuned-ner_swedish_small_set_health_and_prices	Nonzerophilip	2022-07-08T14:01:49Z	4	0	transformers	[ "transformers", "pytorch", "tensorboard", "bert", "token-classification", "generated_from_trainer", "autotrain_compatible", "endpoints_compatible", "region:us" ]	token-classification	2022-07-08T10:53:18Z	--- tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: bert-finetuned-ner_swedish_small_set_health_and_prices results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # bert-finetuned-ner_swedish_small_set_health_and_prices This model is a fine-tuned version of [KBLab/bert-base-swedish-cased-ner](https://huggingface.co/KBLab/bert-base-swedish-cased-ner) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0942 - Precision: 0.7709 - Recall: 0.8118 - F1: 0.7908 - Accuracy: 0.9741 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Precision \| Recall \| F1 \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:---------:\|:------:\|:------:\|:--------:\| \| No log \| 1.0 \| 250 \| 0.1310 \| 0.6116 \| 0.7471 \| 0.6726 \| 0.9578 \| \| 0.1583 \| 2.0 \| 500 \| 0.0939 \| 0.7560 \| 0.8020 \| 0.7783 \| 0.9737 \| \| 0.1583 \| 3.0 \| 750 \| 0.0942 \| 0.7709 \| 0.8118 \| 0.7908 \| 0.9741 \| ### Framework versions - Transformers 4.19.3 - Pytorch 1.7.1 - Datasets 2.2.2 - Tokenizers 0.12.1
malteos/gpt2-xl-german-covid-19	malteos	2022-07-08T13:48:32Z	7	0	transformers	[ "transformers", "pytorch", "gpt2", "text-generation", "de", "license:mit", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2022-07-08T13:14:23Z	--- license: mit language: de widget: - text: "Noch Wochen nach einer Erkrankung an COVID-19 können " --- # German Covid-19 GPT2-XL (1.5B) - Covid-19 specific version of [`malteos/gpt2-xl-wechsel-german`](https://huggingface.co/malteos/gpt2-xl-wechsel-german) - Fine-tuned on 2 GB text from OSCAR filtered for covid related terms. ### How to use You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we set a seed for reproducibility: ```python >>> from transformers import pipeline, set_seed >>> generator = pipeline('text-generation', model='malteos/gpt2-xl-german-covid-19') >>> set_seed(42) >>> generator("Hello, I'm a language model,", max_length=30, num_return_sequences=5) ``` ## License MIT
jonatasgrosman/exp_w2v2t_th_vp-es_s26	jonatasgrosman	2022-07-08T13:44:23Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T12:25:24Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-es_s26 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
Guillaume63/Reinforce-cartpole	Guillaume63	2022-07-08T13:06:18Z	0	0	null	[ "CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class", "model-index", "region:us" ]	reinforcement-learning	2022-07-06T12:59:13Z	--- tags: - CartPole-v1 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinforce-cartpole results: - metrics: - type: mean_reward value: 500.00 +/- 0.00 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 --- # Reinforce Agent playing CartPole-v1 This is a trained model of a Reinforce agent playing CartPole-v1 . To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit5
ramonzaca/testpyramidsrnd	ramonzaca	2022-07-08T12:16:14Z	11	0	ml-agents	[ "ml-agents", "tensorboard", "onnx", "unity-ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids", "region:us" ]	reinforcement-learning	2022-07-08T12:16:09Z	--- tags: - unity-ml-agents - ml-agents - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Pyramids library_name: ml-agents --- # ppo Agent playing Pyramids This is a trained model of a ppo agent playing Pyramids using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://github.com/huggingface/ml-agents#get-started We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: ### Resume the training ``` mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent playing directly in your browser:. 1. Go to https://huggingface.co/spaces/unity/ML-Agents-Pyramids 2. Step 1: Write your model_id: ramonzaca/testpyramidsrnd 3. Step 2: Select your .nn /.onnx file 4. Click on Watch the agent play 👀
dminiotas05/distilbert-base-uncased-finetuned-ft650_6class	dminiotas05	2022-07-08T12:11:05Z	3	0	transformers	[ "transformers", "pytorch", "tensorboard", "distilbert", "text-classification", "generated_from_trainer", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2022-07-08T11:46:36Z	--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-ft650_6class results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # distilbert-base-uncased-finetuned-ft650_6class This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.4555 - Accuracy: 0.3707 - F1: 0.3625 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| F1 \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\|:------:\| \| 1.5838 \| 1.0 \| 188 \| 1.5235 \| 0.3253 \| 0.2947 \| \| 1.4521 \| 2.0 \| 376 \| 1.4744 \| 0.3467 \| 0.3234 \| \| 1.3838 \| 3.0 \| 564 \| 1.4565 \| 0.358 \| 0.3483 \| \| 1.323 \| 4.0 \| 752 \| 1.4555 \| 0.3707 \| 0.3625 \| ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1
jourlin/wiki2json	jourlin	2022-07-08T11:46:44Z	6	0	transformers	[ "transformers", "pytorch", "t5", "text2text-generation", "generated_from_trainer", "dataset:opus_books", "license:apache-2.0", "model-index", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text2text-generation	2022-07-08T06:58:40Z	--- license: apache-2.0 tags: - generated_from_trainer datasets: - opus_books metrics: - bleu model-index: - name: wiki2json results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: opus_books type: opus_books args: en-fr metrics: - name: Bleu type: bleu value: 4.8968 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # wiki2json This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the opus_books dataset. It achieves the following results on the evaluation set: - Loss: 1.6848 - Bleu: 4.8968 - Gen Len: 17.6362 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Bleu \| Gen Len \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:------:\|:-------:\| \| 1.9187 \| 1.0 \| 3178 \| 1.6848 \| 4.8968 \| 17.6362 \| ### Framework versions - Transformers 4.18.0 - Pytorch 1.10.2+cu102 - Datasets 2.3.2 - Tokenizers 0.12.1
jonatasgrosman/exp_w2v2t_th_unispeech-ml_s256	jonatasgrosman	2022-07-08T11:28:09Z	3	0	transformers	[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T11:27:41Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_unispeech-ml_s256 Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_wavlm_s904	jonatasgrosman	2022-07-08T11:25:12Z	5	0	transformers	[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T11:23:56Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_wavlm_s904 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_wavlm_s847	jonatasgrosman	2022-07-08T11:21:22Z	4	0	transformers	[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T11:20:15Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_wavlm_s847 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_vp-sv_s884	jonatasgrosman	2022-07-08T11:04:20Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T11:03:49Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-sv_s884 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_vp-sv_s635	jonatasgrosman	2022-07-08T11:01:14Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T11:00:49Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-sv_s635 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_vp-sv_s946	jonatasgrosman	2022-07-08T10:58:13Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T10:57:48Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-sv_s946 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_hubert_s533	jonatasgrosman	2022-07-08T10:52:20Z	4	0	transformers	[ "transformers", "pytorch", "hubert", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T10:51:52Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_hubert_s533 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_unispeech_s131	jonatasgrosman	2022-07-08T10:45:46Z	3	0	transformers	[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T10:45:06Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_unispeech_s131 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_unispeech_s328	jonatasgrosman	2022-07-08T10:39:17Z	4	0	transformers	[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T10:38:31Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_unispeech_s328 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_xlsr-53_s201	jonatasgrosman	2022-07-08T10:31:19Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T10:30:49Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_xlsr-53_s201 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_xlsr-53_s711	jonatasgrosman	2022-07-08T10:27:24Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T10:26:54Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_xlsr-53_s711 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_vp-100k_s630	jonatasgrosman	2022-07-08T10:24:25Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T10:23:54Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-100k_s630 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_vp-100k_s497	jonatasgrosman	2022-07-08T10:21:24Z	5	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T10:20:58Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-100k_s497 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_th_wav2vec2_s664	jonatasgrosman	2022-07-08T10:06:53Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T10:06:28Z	--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_wav2vec2_s664 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
swtx/ernie-gram-chinese	swtx	2022-07-08T09:44:33Z	5	0	transformers	[ "transformers", "pytorch", "bert", "feature-extraction", "arxiv:2010.12148", "endpoints_compatible", "region:us" ]	feature-extraction	2022-07-08T09:09:46Z	--- language: chinese --- # ERNIE-Gram-chinese ## Introduction ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding More detail: https://arxiv.org/abs/2010.12148 ## Released Model Info \|Model Name\|Language\|Model Structure\| \|:---:\|:---:\|:---:\| \|ernie-gram-chinese\| Chinese \|Layer:12, Hidden:768, Heads:12\| This released Pytorch model is converted from the officially released PaddlePaddle ERNIE model and a series of experiments have been conducted to check the accuracy of the conversion. - Official PaddlePaddle ERNIE repo: https://github.com/PaddlePaddle/ERNIE - Pytorch Conversion repo: https://github.com/nghuyong/ERNIE-Pytorch ## How to use ```Python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("swtx/ernie-gram-chinese") model = AutoModel.from_pretrained("swtx/ernie-gram-chinese") ```
jonatasgrosman/exp_w2v2t_en_r-wav2vec2_s44	jonatasgrosman	2022-07-08T09:36:19Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T09:35:33Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_r-wav2vec2_s44 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_r-wav2vec2_s93	jonatasgrosman	2022-07-08T09:28:53Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T09:28:09Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_r-wav2vec2_s93 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
epsil/testpyramidsrnd	epsil	2022-07-08T09:27:21Z	4	0	ml-agents	[ "ml-agents", "tensorboard", "onnx", "unity-ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids", "region:us" ]	reinforcement-learning	2022-07-08T09:27:16Z	--- tags: - unity-ml-agents - ml-agents - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Pyramids library_name: ml-agents --- # ppo Agent playing Pyramids This is a trained model of a ppo agent playing Pyramids using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://github.com/huggingface/ml-agents#get-started We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: ### Resume the training ``` mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent playing directly in your browser:. 1. Go to https://huggingface.co/spaces/unity/ML-Agents-Pyramids 2. Step 1: Write your model_id: epsil/testpyramidsrnd 3. Step 2: Select your .nn /.onnx file 4. Click on Watch the agent play 👀
jonatasgrosman/exp_w2v2t_en_r-wav2vec2_s863	jonatasgrosman	2022-07-08T09:19:20Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T09:18:31Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_r-wav2vec2_s863 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459	jonatasgrosman	2022-07-08T08:46:57Z	5	0	transformers	[ "transformers", "pytorch", "unispeech-sat", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T08:46:09Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_unispeech-sat_s459 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_unispeech-sat_s456	jonatasgrosman	2022-07-08T08:26:50Z	6	0	transformers	[ "transformers", "pytorch", "unispeech-sat", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T08:26:01Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_unispeech-sat_s456 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
Shenghao1993/distilbert-base-uncased-finetuned-clinc	Shenghao1993	2022-07-08T08:22:36Z	23	0	transformers	[ "transformers", "pytorch", "tensorboard", "distilbert", "text-classification", "generated_from_trainer", "dataset:clinc_oos", "license:apache-2.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2022-07-06T15:20:11Z	--- license: apache-2.0 tags: - generated_from_trainer datasets: - clinc_oos metrics: - accuracy model-index: - name: distilbert-base-uncased-finetuned-clinc results: - task: name: Text Classification type: text-classification dataset: name: clinc_oos type: clinc_oos args: plus metrics: - name: Accuracy type: accuracy value: 0.9174193548387096 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # distilbert-base-uncased-finetuned-clinc This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset. It achieves the following results on the evaluation set: - Loss: 0.7711 - Accuracy: 0.9174 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| No log \| 1.0 \| 318 \| 3.2830 \| 0.7426 \| \| 3.785 \| 2.0 \| 636 \| 1.8728 \| 0.8410 \| \| 3.785 \| 3.0 \| 954 \| 1.1555 \| 0.8913 \| \| 1.6902 \| 4.0 \| 1272 \| 0.8530 \| 0.9126 \| \| 0.901 \| 5.0 \| 1590 \| 0.7711 \| 0.9174 \| ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1
jonatasgrosman/exp_w2v2t_en_vp-nl_s281	jonatasgrosman	2022-07-08T08:09:32Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T08:08:43Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-nl_s281 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_vp-es_s186	jonatasgrosman	2022-07-08T07:54:17Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T07:53:28Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-es_s186 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_vp-es_s474	jonatasgrosman	2022-07-08T07:45:27Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T07:44:40Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-es_s474 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
ClassCat/roberta-base-french	ClassCat	2022-07-08T07:34:58Z	7	1	transformers	[ "transformers", "pytorch", "roberta", "fill-mask", "fr", "dataset:wikipedia", "dataset:cc100", "license:cc-by-sa-4.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	fill-mask	2022-07-04T17:58:21Z	--- language: fr license: cc-by-sa-4.0 datasets: - wikipedia - cc100 widget: - text: "Je vais à la <mask>." - text: "J'aime le <mask>." - text: "J'ai ouvert la <mask>." - text: "Je m'appelle <mask>." - text: "J'ai beaucoup d'<mask>." --- ## RoBERTa French base model (Uncased) ### Prerequisites transformers==4.19.2 ### Model architecture This model uses RoBERTa base setttings except vocabulary size. ### Tokenizer Using BPE tokenizer with vocabulary size 50,000. ### Training Data * [wiki40b/fr](https://www.tensorflow.org/datasets/catalog/wiki40b#wiki40bfr) (French Wikipedia) * Subset of [CC-100/fr](https://data.statmt.org/cc-100/) : Monolingual Datasets from Web Crawl Data ### Usage ```python from transformers import pipeline unmasker = pipeline('fill-mask', model='ClassCat/roberta-base-french') unmasker("Je vais à la <mask>.") ```
jonatasgrosman/exp_w2v2t_en_vp-fr_s691	jonatasgrosman	2022-07-08T07:20:48Z	5	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T07:20:01Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-fr_s691 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_unispeech-ml_s377	jonatasgrosman	2022-07-08T06:52:52Z	3	0	transformers	[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T06:52:07Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_unispeech-ml_s377 Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_wavlm_s990	jonatasgrosman	2022-07-08T06:48:30Z	4	0	transformers	[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T06:47:43Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_wavlm_s990 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_wavlm_s461	jonatasgrosman	2022-07-08T06:40:13Z	5	0	transformers	[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T06:39:25Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_wavlm_s461 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_wavlm_s767	jonatasgrosman	2022-07-08T06:33:36Z	3	0	transformers	[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T06:32:43Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_wavlm_s767 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_no-pretraining_s883	jonatasgrosman	2022-07-08T06:16:41Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T06:16:14Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_no-pretraining_s883 Fine-tuned randomly initialized wav2vec2 model for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_vp-sv_s438	jonatasgrosman	2022-07-08T06:11:38Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T06:11:10Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-sv_s438 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_hubert_s875	jonatasgrosman	2022-07-08T05:46:21Z	3	0	transformers	[ "transformers", "pytorch", "hubert", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T05:45:44Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_hubert_s875 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_unispeech_s227	jonatasgrosman	2022-07-08T05:36:00Z	4	0	transformers	[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T05:35:18Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_unispeech_s227 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
phyous/q-Taxi-v3-2	phyous	2022-07-08T05:32:54Z	0	0	null	[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2022-07-08T05:27:28Z	--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-Taxi-v3-2 results: - metrics: - type: mean_reward value: 7.56 +/- 2.71 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 --- # Q-Learning Agent playing Taxi-v3 This is a trained model of a Q-Learning agent playing Taxi-v3 . ## Usage ```python model = load_from_hub(repo_id="phyous/q-Taxi-v3-2", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) evaluate_agent(env, model["max_steps"], model["n_eval_episodes"], model["qtable"], model["eval_seed"]) ```
jonatasgrosman/exp_w2v2t_en_unispeech_s870	jonatasgrosman	2022-07-08T05:31:32Z	4	0	transformers	[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T05:30:42Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_unispeech_s870 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
phyous/q-Taxi-v3	phyous	2022-07-08T05:12:47Z	0	0	null	[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2022-07-08T05:12:07Z	--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-Taxi-v3 results: - metrics: - type: mean_reward value: 7.44 +/- 2.74 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 --- # Q-Learning Agent playing Taxi-v3 This is a trained model of a Q-Learning agent playing Taxi-v3 . ## Usage ```python model = load_from_hub(repo_id="phyous/q-Taxi-v3", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) evaluate_agent(env, model["max_steps"], model["n_eval_episodes"], model["qtable"], model["eval_seed"]) ```
jonatasgrosman/exp_w2v2t_en_xlsr-53_s870	jonatasgrosman	2022-07-08T05:07:22Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T05:06:55Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_xlsr-53_s870 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
ChauNguyen23/phobert-base-finetuned-imdb	ChauNguyen23	2022-07-08T05:03:20Z	4	0	transformers	[ "transformers", "pytorch", "tensorboard", "roberta", "fill-mask", "generated_from_trainer", "dataset:imdb", "autotrain_compatible", "endpoints_compatible", "region:us" ]	fill-mask	2022-07-08T04:47:50Z	--- tags: - generated_from_trainer datasets: - imdb model-index: - name: phobert-base-finetuned-imdb results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # phobert-base-finetuned-imdb This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the imdb dataset. It achieves the following results on the evaluation set: - Loss: 2.6149 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3.0 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:-----:\|:----:\|:---------------:\| \| 3.3266 \| 1.0 \| 157 \| 2.7949 \| \| 2.9162 \| 2.0 \| 314 \| 2.6515 \| \| 2.8177 \| 3.0 \| 471 \| 2.6452 \| ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1
jonatasgrosman/exp_w2v2t_en_vp-100k_s364	jonatasgrosman	2022-07-08T04:56:51Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T04:56:25Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-100k_s364 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
rserenity/shuukobot	rserenity	2022-07-08T04:38:26Z	0	0	null	[ "tensorboard", "text-generation", "region:us" ]	text-generation	2022-07-08T02:58:22Z	--- tags: - text-generation ---
jonatasgrosman/exp_w2v2t_en_wav2vec2_s203	jonatasgrosman	2022-07-08T04:24:19Z	3	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T04:23:34Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_wav2vec2_s203 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_en_wav2vec2_s924	jonatasgrosman	2022-07-08T04:12:02Z	4	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2022-07-08T03:56:41Z	--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_wav2vec2_s924 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
okho0653/Bio_ClinicalBERT-zero-shot-tokenizer-truncation-sentiment-model	okho0653	2022-07-08T03:54:48Z	6	0	transformers	[ "transformers", "pytorch", "tensorboard", "bert", "text-classification", "generated_from_trainer", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2022-07-08T01:09:10Z	--- license: mit tags: - generated_from_trainer model-index: - name: Bio_ClinicalBERT-zero-shot-tokenizer-truncation-sentiment-model results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Bio_ClinicalBERT-zero-shot-tokenizer-truncation-sentiment-model This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1

jonatasgrosman/exp_w2v2t_it_vp-100k_s449

jonatasgrosman

2022-07-08T19:01:30Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T19:00:43Z

--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-100k_s449 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_it_vp-100k_s149

jonatasgrosman

2022-07-08T18:56:07Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T18:55:24Z

--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-100k_s149 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

domenicrosati/SPECTER-with-biblio-context-finetuned-review_classifier

domenicrosati

2022-07-08T18:53:09Z

27

0

transformers

[ "transformers", "pytorch", "bert", "text-classification", "generated_from_trainer", "license:apache-2.0", "endpoints_compatible", "region:us" ]

text-classification

2022-07-08T13:43:12Z

--- license: apache-2.0 tags: - text-classification - generated_from_trainer metrics: - accuracy - f1 - recall - precision model-index: - name: SPECTER-with-biblio-context-finetuned-review_classifier results: [] ---  # SPECTER-with-biblio-context-finetuned-review_classifier This model is a fine-tuned version of [allenai/specter](https://huggingface.co/allenai/specter) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1284 - Accuracy: 0.962 - F1: 0.7892 - Recall: 0.7593 - Precision: 0.8216 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 4.5e-05 - train_batch_size: 12 - eval_batch_size: 12 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 1000 - num_epochs: 2 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:---------:| | 0.1956 | 1.0 | 6667 | 0.1805 | 0.9514 | 0.7257 | 0.6860 | 0.7702 | | 0.135 | 2.0 | 13334 | 0.1284 | 0.962 | 0.7892 | 0.7593 | 0.8216 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.12.0+cu102 - Datasets 2.3.2 - Tokenizers 0.12.1

saekomdalkom/long-t5-local-base-finetuned

saekomdalkom

2022-07-08T18:48:45Z

5

0

transformers

[ "transformers", "pytorch", "longt5", "text2text-generation", "generated_from_trainer", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text2text-generation

2022-07-01T05:40:08Z

--- license: apache-2.0 tags: - generated_from_trainer metrics: - rouge model-index: - name: long-t5-local-base-finetuned results: [] ---  # long-t5-local-base-finetuned This model is a fine-tuned version of [google/long-t5-local-base](https://huggingface.co/google/long-t5-local-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 9.2722 - Rouge1: 3.8848 - Rouge2: 0.5914 - Rougel: 3.5038 - Rougelsum: 3.7022 - Gen Len: 19.0 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-06 - train_batch_size: 3 - eval_batch_size: 3 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | No log | 0.16 | 100 | 342.4395 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | | No log | 0.31 | 200 | 323.6985 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | | No log | 0.47 | 300 | 303.8767 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | | No log | 0.62 | 400 | 284.7559 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | | 295.8376 | 0.78 | 500 | 263.0420 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | | 295.8376 | 0.93 | 600 | 243.2220 | 0.0242 | 0.0 | 0.0223 | 0.0242 | 19.0 | | 295.8376 | 1.09 | 700 | 224.4514 | 0.0493 | 0.0 | 0.0507 | 0.0513 | 19.0 | | 295.8376 | 1.24 | 800 | 203.9065 | 0.0656 | 0.0 | 0.0634 | 0.0658 | 19.0 | | 295.8376 | 1.4 | 900 | 184.8686 | 0.0609 | 0.0 | 0.058 | 0.0616 | 19.0 | | 199.938 | 1.55 | 1000 | 167.5315 | 0.0638 | 0.0 | 0.0626 | 0.063 | 19.0 | | 199.938 | 1.71 | 1100 | 151.2369 | 0.0421 | 0.0 | 0.0411 | 0.0413 | 19.0 | | 199.938 | 1.86 | 1200 | 137.2366 | 0.0358 | 0.0 | 0.0346 | 0.0342 | 19.0 | | 199.938 | 2.02 | 1300 | 125.3076 | 0.0173 | 0.0 | 0.0157 | 0.0157 | 19.0 | | 199.938 | 2.17 | 1400 | 114.5600 | 0.0173 | 0.0 | 0.0157 | 0.0157 | 19.0 | | 136.1309 | 2.33 | 1500 | 105.9237 | 0.0361 | 0.0 | 0.0344 | 0.0363 | 19.0 | | 136.1309 | 2.48 | 1600 | 97.4123 | 0.0526 | 0.0 | 0.051 | 0.054 | 19.0 | | 136.1309 | 2.64 | 1700 | 89.0873 | 0.0427 | 0.0 | 0.0407 | 0.0418 | 19.0 | | 136.1309 | 2.79 | 1800 | 82.0562 | 0.0496 | 0.0 | 0.0462 | 0.0462 | 19.0 | | 136.1309 | 2.95 | 1900 | 76.2360 | 0.0361 | 0.0 | 0.0345 | 0.0363 | 19.0 | | 99.2229 | 3.1 | 2000 | 70.0604 | 0.0438 | 0.0 | 0.0425 | 0.0439 | 19.0 | | 99.2229 | 3.26 | 2100 | 65.1038 | 0.0454 | 0.0 | 0.0441 | 0.0447 | 19.0 | | 99.2229 | 3.41 | 2200 | 59.1831 | 0.0344 | 0.0 | 0.0318 | 0.0318 | 19.0 | | 99.2229 | 3.57 | 2300 | 53.0313 | 0.0471 | 0.0 | 0.0448 | 0.0454 | 19.0 | | 99.2229 | 3.72 | 2400 | 48.2110 | 0.0369 | 0.0 | 0.0369 | 0.0369 | 19.0 | | 73.4208 | 3.88 | 2500 | 44.2004 | 0.0425 | 0.0 | 0.0427 | 0.044 | 19.0 | | 73.4208 | 4.03 | 2600 | 40.1925 | 0.0632 | 0.0 | 0.0619 | 0.0612 | 19.0 | | 73.4208 | 4.19 | 2700 | 36.3698 | 0.0887 | 0.0 | 0.0873 | 0.086 | 19.0 | | 73.4208 | 4.34 | 2800 | 33.2154 | 0.164 | 0.0 | 0.1652 | 0.1705 | 19.0 | | 73.4208 | 4.5 | 2900 | 30.9366 | 0.1106 | 0.0 | 0.1138 | 0.1144 | 19.0 | | 55.6661 | 4.65 | 3000 | 28.5672 | 0.1289 | 0.0 | 0.1295 | 0.131 | 19.0 | | 55.6661 | 4.81 | 3100 | 27.0910 | 0.2501 | 0.0 | 0.2514 | 0.2527 | 19.0 | | 55.6661 | 4.96 | 3200 | 25.6666 | 0.318 | 0.0 | 0.3322 | 0.3203 | 19.0 | | 55.6661 | 5.12 | 3300 | 24.6176 | 0.6319 | 0.0 | 0.6419 | 0.6299 | 19.0 | | 55.6661 | 5.27 | 3400 | 23.6474 | 1.6632 | 0.0033 | 1.665 | 1.6244 | 19.0 | | 45.1105 | 5.43 | 3500 | 22.7063 | 3.1374 | 0.0 | 3.1331 | 3.1333 | 19.0 | | 45.1105 | 5.58 | 3600 | 21.9191 | 5.0757 | 0.0 | 5.0694 | 5.0456 | 19.0 | | 45.1105 | 5.74 | 3700 | 21.3359 | 5.6576 | 0.0 | 5.689 | 5.6772 | 19.0 | | 45.1105 | 5.89 | 3800 | 20.6990 | 5.828 | 0.0 | 5.8801 | 5.8688 | 19.0 | | 45.1105 | 6.05 | 3900 | 20.1800 | 6.3727 | 0.0 | 6.3801 | 6.3716 | 19.0 | | 39.6923 | 6.2 | 4000 | 19.7415 | 6.2209 | 0.0 | 6.2347 | 6.2368 | 19.0 | | 39.6923 | 6.36 | 4100 | 19.2800 | 5.7215 | 0.0 | 5.7452 | 5.7295 | 19.0 | | 39.6923 | 6.51 | 4200 | 18.9683 | 6.1018 | 0.0062 | 6.1 | 6.0935 | 19.0 | | 39.6923 | 6.67 | 4300 | 18.5776 | 6.0354 | 0.0062 | 6.0227 | 6.0103 | 19.0 | | 39.6923 | 6.82 | 4400 | 18.2629 | 5.4438 | 0.0062 | 5.441 | 5.4629 | 19.0 | | 36.1688 | 6.98 | 4500 | 18.0268 | 5.3214 | 0.0091 | 5.3093 | 5.2992 | 19.0 | | 36.1688 | 7.13 | 4600 | 17.7740 | 5.2223 | 0.0123 | 5.2132 | 5.2084 | 19.0 | | 36.1688 | 7.29 | 4700 | 17.5345 | 5.178 | 0.0231 | 5.1615 | 5.1243 | 19.0 | | 36.1688 | 7.44 | 4800 | 17.3846 | 5.3899 | 0.0277 | 5.3414 | 5.3534 | 19.0 | | 36.1688 | 7.6 | 4900 | 17.1999 | 5.315 | 0.0272 | 5.2572 | 5.2477 | 19.0 | | 33.5745 | 7.75 | 5000 | 17.0078 | 5.9014 | 0.028 | 5.8181 | 5.8058 | 19.0 | | 33.5745 | 7.91 | 5100 | 16.6418 | 5.7546 | 0.0242 | 5.6903 | 5.6746 | 19.0 | | 33.5745 | 8.06 | 5200 | 16.6330 | 6.6893 | 0.0182 | 6.6354 | 6.6178 | 19.0 | | 33.5745 | 8.22 | 5300 | 16.3423 | 6.1679 | 0.0072 | 6.1518 | 6.128 | 19.0 | | 33.5745 | 8.37 | 5400 | 16.2373 | 6.7659 | 0.0139 | 6.7271 | 6.7076 | 19.0 | | 31.9486 | 8.53 | 5500 | 16.1523 | 7.1991 | 0.0139 | 7.1674 | 7.1283 | 19.0 | | 31.9486 | 8.68 | 5600 | 16.0607 | 7.7042 | 0.0169 | 7.6741 | 7.6537 | 19.0 | | 31.9486 | 8.84 | 5700 | 15.7647 | 7.1238 | 0.02 | 7.1113 | 7.0586 | 19.0 | | 31.9486 | 8.99 | 5800 | 15.6194 | 7.3055 | 0.0116 | 7.3311 | 7.2683 | 19.0 | | 31.9486 | 9.15 | 5900 | 15.4994 | 7.3365 | 0.0139 | 7.3026 | 7.2708 | 19.0 | | 30.5224 | 9.3 | 6000 | 15.4207 | 8.1959 | 0.0116 | 8.1917 | 8.1651 | 19.0 | | 30.5224 | 9.46 | 6100 | 15.2981 | 7.7936 | 0.0144 | 7.7826 | 7.7488 | 19.0 | | 30.5224 | 9.61 | 6200 | 15.2391 | 7.95 | 0.0144 | 7.9371 | 7.895 | 19.0 | | 30.5224 | 9.77 | 6300 | 15.0941 | 7.1669 | 0.0144 | 7.146 | 7.1251 | 19.0 | | 30.5224 | 9.92 | 6400 | 14.9979 | 6.2157 | 0.0076 | 6.2086 | 6.1774 | 19.0 | | 29.1236 | 10.08 | 6500 | 14.9523 | 7.4422 | 0.0137 | 7.3929 | 7.393 | 19.0 | | 29.1236 | 10.23 | 6600 | 14.9515 | 7.2375 | 0.0137 | 7.1728 | 7.1779 | 19.0 | | 29.1236 | 10.39 | 6700 | 14.8874 | 7.5071 | 0.0068 | 7.4544 | 7.4739 | 19.0 | | 29.1236 | 10.54 | 6800 | 14.8057 | 5.9608 | 0.0169 | 5.8754 | 5.8691 | 19.0 | | 29.1236 | 10.7 | 6900 | 14.6818 | 5.6345 | 0.021 | 5.5422 | 5.5331 | 19.0 | | 28.314 | 10.85 | 7000 | 14.5409 | 5.5799 | 0.0169 | 5.4915 | 5.4833 | 19.0 | | 28.314 | 11.01 | 7100 | 14.4512 | 4.3498 | 0.0368 | 4.2243 | 4.2193 | 19.0 | | 28.314 | 11.16 | 7200 | 14.4560 | 4.0453 | 0.0372 | 3.9481 | 3.9228 | 19.0 | | 28.314 | 11.32 | 7300 | 14.3851 | 5.1332 | 0.0426 | 5.0186 | 4.9882 | 19.0 | | 28.314 | 11.47 | 7400 | 14.2265 | 4.8944 | 0.0371 | 4.7869 | 4.7765 | 19.0 | | 27.5349 | 11.63 | 7500 | 14.1214 | 3.8846 | 0.0335 | 3.7882 | 3.7677 | 19.0 | | 27.5349 | 11.78 | 7600 | 14.1505 | 3.9992 | 0.0514 | 3.883 | 3.8385 | 19.0 | | 27.5349 | 11.94 | 7700 | 13.9923 | 3.4526 | 0.0664 | 3.325 | 3.3258 | 19.0 | | 27.5349 | 12.09 | 7800 | 14.0299 | 2.3086 | 0.0346 | 2.25 | 2.219 | 19.0 | | 27.5349 | 12.25 | 7900 | 13.9814 | 2.4402 | 0.0628 | 2.3282 | 2.3004 | 19.0 | | 26.4286 | 12.4 | 8000 | 13.8561 | 2.9869 | 0.0654 | 2.8769 | 2.8485 | 19.0 | | 26.4286 | 12.56 | 8100 | 13.8259 | 1.9609 | 0.0386 | 1.8863 | 1.8846 | 19.0 | | 26.4286 | 12.71 | 8200 | 13.8127 | 2.0628 | 0.0355 | 1.9915 | 1.9738 | 19.0 | | 26.4286 | 12.87 | 8300 | 13.7174 | 1.9904 | 0.081 | 1.888 | 1.9069 | 19.0 | | 26.4286 | 13.02 | 8400 | 13.6308 | 2.1398 | 0.1055 | 2.0204 | 2.0468 | 19.0 | | 26.108 | 13.18 | 8500 | 13.6490 | 1.8934 | 0.0788 | 1.7942 | 1.8188 | 19.0 | | 26.108 | 13.33 | 8600 | 13.5996 | 1.8746 | 0.0901 | 1.7441 | 1.8006 | 19.0 | | 26.108 | 13.49 | 8700 | 13.5394 | 1.7846 | 0.0895 | 1.6648 | 1.7331 | 19.0 | | 26.108 | 13.64 | 8800 | 13.5368 | 2.1345 | 0.1287 | 1.9808 | 2.0814 | 19.0 | | 26.108 | 13.8 | 8900 | 13.4793 | 2.5234 | 0.1611 | 2.3289 | 2.4292 | 19.0 | | 25.4931 | 13.95 | 9000 | 13.3633 | 2.8056 | 0.1953 | 2.5619 | 2.7088 | 19.0 | | 25.4931 | 14.11 | 9100 | 13.5182 | 3.087 | 0.2192 | 2.8182 | 2.9928 | 19.0 | | 25.4931 | 14.26 | 9200 | 13.3372 | 2.6353 | 0.175 | 2.4145 | 2.589 | 19.0 | | 25.4931 | 14.42 | 9300 | 13.2822 | 2.7577 | 0.1905 | 2.5277 | 2.7215 | 19.0 | | 25.4931 | 14.57 | 9400 | 13.2011 | 3.1891 | 0.2381 | 2.9276 | 3.142 | 19.0 | | 24.9241 | 14.73 | 9500 | 13.2201 | 2.609 | 0.1683 | 2.4162 | 2.5905 | 19.0 | | 24.9241 | 14.88 | 9600 | 13.2206 | 3.1083 | 0.2241 | 2.8627 | 3.0606 | 19.0 | | 24.9241 | 15.04 | 9700 | 13.2157 | 3.6233 | 0.2731 | 3.338 | 3.5642 | 19.0 | | 24.9241 | 15.19 | 9800 | 13.1195 | 3.1785 | 0.2318 | 2.9449 | 3.1306 | 19.0 | | 24.9241 | 15.35 | 9900 | 13.0481 | 3.0249 | 0.2192 | 2.7991 | 2.9925 | 19.0 | | 24.4511 | 15.5 | 10000 | 13.0693 | 3.1189 | 0.2287 | 2.8726 | 3.0669 | 19.0 | | 24.4511 | 15.66 | 10100 | 12.9204 | 2.6405 | 0.1899 | 2.4337 | 2.61 | 19.0 | | 24.4511 | 15.81 | 10200 | 12.9200 | 2.9037 | 0.2148 | 2.6775 | 2.8683 | 19.0 | | 24.4511 | 15.97 | 10300 | 12.9203 | 2.8847 | 0.2034 | 2.6586 | 2.8438 | 19.0 | | 24.4511 | 16.12 | 10400 | 12.8723 | 2.8195 | 0.1976 | 2.5922 | 2.7803 | 19.0 | | 23.8949 | 16.28 | 10500 | 12.9749 | 3.2658 | 0.2217 | 2.9905 | 3.2262 | 19.0 | | 23.8949 | 16.43 | 10600 | 12.7975 | 2.9762 | 0.1844 | 2.7295 | 2.9474 | 19.0 | | 23.8949 | 16.59 | 10700 | 12.7497 | 2.5496 | 0.1406 | 2.3536 | 2.5269 | 19.0 | | 23.8949 | 16.74 | 10800 | 12.6485 | 2.5509 | 0.1454 | 2.343 | 2.5182 | 19.0 | | 23.8949 | 16.9 | 10900 | 12.6574 | 2.1914 | 0.1281 | 2.0113 | 2.1574 | 19.0 | | 23.4963 | 17.05 | 11000 | 12.6919 | 2.1748 | 0.1299 | 1.9909 | 2.1229 | 19.0 | | 23.4963 | 17.21 | 11100 | 12.5660 | 2.3751 | 0.1177 | 2.1417 | 2.326 | 19.0 | | 23.4963 | 17.36 | 11200 | 12.5866 | 2.6893 | 0.1344 | 2.4378 | 2.6318 | 19.0 | | 23.4963 | 17.52 | 11300 | 12.5427 | 2.5546 | 0.1411 | 2.3175 | 2.5073 | 19.0 | | 23.4963 | 17.67 | 11400 | 12.5011 | 2.347 | 0.1223 | 2.1322 | 2.3077 | 19.0 | | 23.1492 | 17.83 | 11500 | 12.5168 | 2.2304 | 0.1141 | 2.0657 | 2.1951 | 19.0 | | 23.1492 | 17.98 | 11600 | 12.4043 | 2.4485 | 0.1209 | 2.2548 | 2.4114 | 19.0 | | 23.1492 | 18.14 | 11700 | 12.4192 | 2.0551 | 0.0887 | 1.8996 | 2.0199 | 19.0 | | 23.1492 | 18.29 | 11800 | 12.3799 | 2.1076 | 0.0932 | 1.9464 | 2.0589 | 19.0 | | 23.1492 | 18.45 | 11900 | 12.4263 | 2.4136 | 0.1152 | 2.2172 | 2.357 | 19.0 | | 22.7005 | 18.6 | 12000 | 12.3218 | 2.1197 | 0.1105 | 1.9997 | 2.0873 | 19.0 | | 22.7005 | 18.76 | 12100 | 12.3297 | 2.1883 | 0.1102 | 2.0414 | 2.1267 | 19.0 | | 22.7005 | 18.91 | 12200 | 12.3026 | 1.966 | 0.0954 | 1.8387 | 1.9469 | 19.0 | | 22.7005 | 19.07 | 12300 | 12.3030 | 2.0179 | 0.0955 | 1.8834 | 1.9858 | 19.0 | | 22.7005 | 19.22 | 12400 | 12.2478 | 1.9549 | 0.0948 | 1.8437 | 1.9092 | 19.0 | | 22.3178 | 19.38 | 12500 | 12.1803 | 1.6396 | 0.0648 | 1.5296 | 1.6208 | 19.0 | | 22.3178 | 19.53 | 12600 | 12.1732 | 1.5568 | 0.0769 | 1.4894 | 1.5387 | 19.0 | | 22.3178 | 19.69 | 12700 | 12.1342 | 1.6861 | 0.0782 | 1.6105 | 1.666 | 19.0 | | 22.3178 | 19.84 | 12800 | 12.1313 | 2.023 | 0.0965 | 1.9295 | 2.0072 | 19.0 | | 22.3178 | 20.0 | 12900 | 12.1315 | 1.5878 | 0.0701 | 1.5153 | 1.5467 | 19.0 | | 21.8344 | 20.16 | 13000 | 12.0611 | 1.6406 | 0.0637 | 1.5665 | 1.6033 | 19.0 | | 21.8344 | 20.31 | 13100 | 12.0327 | 1.5913 | 0.0544 | 1.5209 | 1.552 | 19.0 | | 21.8344 | 20.47 | 13200 | 12.0466 | 1.3618 | 0.0494 | 1.3186 | 1.33 | 19.0 | | 21.8344 | 20.62 | 13300 | 12.0787 | 1.4445 | 0.0451 | 1.4073 | 1.41 | 19.0 | | 21.8344 | 20.78 | 13400 | 11.9829 | 1.3465 | 0.0494 | 1.3247 | 1.3167 | 19.0 | | 21.6309 | 20.93 | 13500 | 11.9072 | 1.4165 | 0.0519 | 1.3761 | 1.3839 | 19.0 | | 21.6309 | 21.09 | 13600 | 11.9261 | 1.3969 | 0.0502 | 1.3606 | 1.3618 | 19.0 | | 21.6309 | 21.24 | 13700 | 11.8313 | 1.3337 | 0.0337 | 1.2974 | 1.316 | 19.0 | | 21.6309 | 21.4 | 13800 | 11.7709 | 1.3045 | 0.0371 | 1.2746 | 1.2889 | 19.0 | | 21.6309 | 21.55 | 13900 | 11.8402 | 1.6106 | 0.0391 | 1.5678 | 1.5697 | 19.0 | | 21.2262 | 21.71 | 14000 | 11.7132 | 1.3261 | 0.0222 | 1.296 | 1.3051 | 19.0 | | 21.2262 | 21.86 | 14100 | 11.7206 | 1.41 | 0.0252 | 1.374 | 1.3985 | 19.0 | | 21.2262 | 22.02 | 14200 | 11.7033 | 1.6231 | 0.0478 | 1.5632 | 1.5851 | 19.0 | | 21.2262 | 22.17 | 14300 | 11.7385 | 1.8974 | 0.0618 | 1.8339 | 1.8583 | 19.0 | | 21.2262 | 22.33 | 14400 | 11.6519 | 1.8998 | 0.0541 | 1.8285 | 1.8552 | 19.0 | | 20.8055 | 22.48 | 14500 | 11.6039 | 1.9561 | 0.0582 | 1.859 | 1.9073 | 19.0 | | 20.8055 | 22.64 | 14600 | 11.6322 | 1.7731 | 0.0442 | 1.7061 | 1.7303 | 19.0 | | 20.8055 | 22.79 | 14700 | 11.6046 | 1.8874 | 0.0618 | 1.8083 | 1.8539 | 19.0 | | 20.8055 | 22.95 | 14800 | 11.5051 | 1.4271 | 0.016 | 1.3996 | 1.4086 | 19.0 | | 20.8055 | 23.1 | 14900 | 11.5564 | 1.743 | 0.0451 | 1.6787 | 1.727 | 19.0 | | 20.6263 | 23.26 | 15000 | 11.5024 | 1.9313 | 0.0575 | 1.8357 | 1.887 | 19.0 | | 20.6263 | 23.41 | 15100 | 11.5281 | 2.082 | 0.0435 | 1.9865 | 2.0327 | 19.0 | | 20.6263 | 23.57 | 15200 | 11.4223 | 1.9773 | 0.0332 | 1.9038 | 1.9432 | 19.0 | | 20.6263 | 23.72 | 15300 | 11.4675 | 1.7845 | 0.0831 | 1.6835 | 1.7414 | 19.0 | | 20.6263 | 23.88 | 15400 | 11.3882 | 2.1183 | 0.0715 | 1.9965 | 2.0725 | 19.0 | | 20.3154 | 24.03 | 15500 | 11.4197 | 2.4045 | 0.1336 | 2.2302 | 2.3024 | 19.0 | | 20.3154 | 24.19 | 15600 | 11.3558 | 1.9596 | 0.1196 | 1.8152 | 1.8748 | 19.0 | | 20.3154 | 24.34 | 15700 | 11.3438 | 2.0931 | 0.111 | 1.9469 | 1.999 | 19.0 | | 20.3154 | 24.5 | 15800 | 11.3021 | 2.2159 | 0.1257 | 2.0511 | 2.1345 | 19.0 | | 20.3154 | 24.65 | 15900 | 11.3178 | 2.093 | 0.132 | 1.9083 | 1.9969 | 19.0 | | 20.0858 | 24.81 | 16000 | 11.2377 | 1.6589 | 0.1129 | 1.5625 | 1.6245 | 19.0 | | 20.0858 | 24.96 | 16100 | 11.2058 | 1.6667 | 0.0854 | 1.5597 | 1.6223 | 19.0 | | 20.0858 | 25.12 | 16200 | 11.1602 | 2.0907 | 0.1219 | 1.9297 | 1.9988 | 19.0 | | 20.0858 | 25.27 | 16300 | 11.1666 | 1.86 | 0.1092 | 1.7398 | 1.7993 | 19.0 | | 20.0858 | 25.43 | 16400 | 11.1807 | 1.8879 | 0.1818 | 1.7579 | 1.8335 | 19.0 | | 19.7588 | 25.58 | 16500 | 11.1310 | 2.0377 | 0.1612 | 1.8653 | 1.9538 | 19.0 | | 19.7588 | 25.74 | 16600 | 11.1577 | 2.1441 | 0.1767 | 1.9546 | 2.0518 | 19.0 | | 19.7588 | 25.89 | 16700 | 11.0748 | 1.8679 | 0.1892 | 1.7249 | 1.7822 | 19.0 | | 19.7588 | 26.05 | 16800 | 11.1048 | 2.2775 | 0.2072 | 2.0566 | 2.1521 | 19.0 | | 19.7588 | 26.2 | 16900 | 11.0498 | 1.8117 | 0.161 | 1.6879 | 1.7357 | 19.0 | | 19.4627 | 26.36 | 17000 | 11.0435 | 1.7875 | 0.1627 | 1.6626 | 1.7306 | 19.0 | | 19.4627 | 26.51 | 17100 | 10.9406 | 1.7333 | 0.1645 | 1.6051 | 1.6671 | 19.0 | | 19.4627 | 26.67 | 17200 | 10.9242 | 1.596 | 0.1426 | 1.4747 | 1.5341 | 19.0 | | 19.4627 | 26.82 | 17300 | 10.9571 | 1.9874 | 0.2109 | 1.8109 | 1.9061 | 19.0 | | 19.4627 | 26.98 | 17400 | 10.9265 | 1.6999 | 0.1353 | 1.5574 | 1.6402 | 19.0 | | 19.2619 | 27.13 | 17500 | 10.8919 | 1.7543 | 0.1709 | 1.587 | 1.6605 | 19.0 | | 19.2619 | 27.29 | 17600 | 10.8382 | 2.126 | 0.2056 | 1.8609 | 2.0021 | 19.0 | | 19.2619 | 27.44 | 17700 | 10.8936 | 1.9626 | 0.1726 | 1.7402 | 1.8665 | 19.0 | | 19.2619 | 27.6 | 17800 | 10.8565 | 1.7668 | 0.1673 | 1.5914 | 1.7099 | 19.0 | | 19.2619 | 27.75 | 17900 | 10.9047 | 2.0972 | 0.1867 | 1.8519 | 2.0224 | 19.0 | | 19.0457 | 27.91 | 18000 | 10.7900 | 2.7761 | 0.2904 | 2.4403 | 2.6936 | 19.0 | | 19.0457 | 28.06 | 18100 | 10.7191 | 2.3652 | 0.2431 | 2.0989 | 2.2767 | 19.0 | | 19.0457 | 28.22 | 18200 | 10.7462 | 3.3125 | 0.361 | 2.847 | 3.1506 | 19.0 | | 19.0457 | 28.37 | 18300 | 10.7721 | 2.9247 | 0.3 | 2.5443 | 2.806 | 19.0 | | 19.0457 | 28.53 | 18400 | 10.7208 | 2.5398 | 0.2812 | 2.2211 | 2.4312 | 19.0 | | 18.8301 | 28.68 | 18500 | 10.6708 | 2.5902 | 0.281 | 2.2765 | 2.4881 | 19.0 | | 18.8301 | 28.84 | 18600 | 10.7220 | 2.276 | 0.2061 | 1.9904 | 2.1922 | 19.0 | | 18.8301 | 28.99 | 18700 | 10.6855 | 2.8678 | 0.3496 | 2.52 | 2.751 | 19.0 | | 18.8301 | 29.15 | 18800 | 10.6550 | 2.5232 | 0.2724 | 2.2108 | 2.4314 | 19.0 | | 18.8301 | 29.3 | 18900 | 10.6488 | 2.5629 | 0.2203 | 2.2361 | 2.4261 | 19.0 | | 18.5872 | 29.46 | 19000 | 10.6123 | 2.5052 | 0.1923 | 2.1381 | 2.3821 | 19.0 | | 18.5872 | 29.61 | 19100 | 10.6105 | 3.7779 | 0.3653 | 3.2404 | 3.5759 | 19.0 | | 18.5872 | 29.77 | 19200 | 10.5823 | 3.8282 | 0.3743 | 3.2645 | 3.6077 | 19.0 | | 18.5872 | 29.92 | 19300 | 10.5606 | 3.0976 | 0.277 | 2.6041 | 2.8838 | 19.0 | | 18.5872 | 30.08 | 19400 | 10.5846 | 3.638 | 0.3482 | 3.0804 | 3.4294 | 19.0 | | 18.2839 | 30.23 | 19500 | 10.4722 | 2.6173 | 0.2326 | 2.2268 | 2.4656 | 19.0 | | 18.2839 | 30.39 | 19600 | 10.5211 | 3.5085 | 0.3377 | 2.9751 | 3.2889 | 19.0 | | 18.2839 | 30.54 | 19700 | 10.4735 | 2.4781 | 0.2097 | 2.1099 | 2.3338 | 19.0 | | 18.2839 | 30.7 | 19800 | 10.4545 | 3.1459 | 0.3022 | 2.6844 | 2.9559 | 19.0 | | 18.2839 | 30.85 | 19900 | 10.4525 | 3.6095 | 0.3637 | 3.0873 | 3.3886 | 19.0 | | 18.1352 | 31.01 | 20000 | 10.4409 | 4.0556 | 0.4621 | 3.3857 | 3.7778 | 19.0 | | 18.1352 | 31.16 | 20100 | 10.4132 | 3.8346 | 0.3863 | 3.2323 | 3.6266 | 19.0 | | 18.1352 | 31.32 | 20200 | 10.4468 | 2.3736 | 0.1977 | 2.0195 | 2.236 | 19.0 | | 18.1352 | 31.47 | 20300 | 10.3896 | 3.6954 | 0.3512 | 3.1402 | 3.4667 | 19.0 | | 18.1352 | 31.63 | 20400 | 10.3546 | 3.5158 | 0.3558 | 3.0575 | 3.3116 | 19.0 | | 17.9834 | 31.78 | 20500 | 10.3632 | 3.179 | 0.3374 | 2.7634 | 2.9846 | 19.0 | | 17.9834 | 31.94 | 20600 | 10.3168 | 3.9121 | 0.4012 | 3.3812 | 3.687 | 19.0 | | 17.9834 | 32.09 | 20700 | 10.2772 | 3.6148 | 0.3667 | 3.1059 | 3.3541 | 19.0 | | 17.9834 | 32.25 | 20800 | 10.3173 | 3.1448 | 0.2924 | 2.6948 | 2.9338 | 19.0 | | 17.9834 | 32.4 | 20900 | 10.2154 | 2.4611 | 0.1922 | 2.1597 | 2.3288 | 19.0 | | 17.6192 | 32.56 | 21000 | 10.2957 | 3.3177 | 0.3762 | 2.8085 | 3.0595 | 19.0 | | 17.6192 | 32.71 | 21100 | 10.2064 | 3.4663 | 0.3819 | 3.0229 | 3.2201 | 19.0 | | 17.6192 | 32.87 | 21200 | 10.2235 | 3.245 | 0.3179 | 2.7618 | 3.0066 | 19.0 | | 17.6192 | 33.02 | 21300 | 10.2193 | 2.5572 | 0.2775 | 2.216 | 2.3892 | 19.0 | | 17.6192 | 33.18 | 21400 | 10.2467 | 3.4873 | 0.3934 | 3.02 | 3.2701 | 19.0 | | 17.5532 | 33.33 | 21500 | 10.2378 | 2.8087 | 0.3049 | 2.4001 | 2.6218 | 19.0 | | 17.5532 | 33.49 | 21600 | 10.2086 | 3.8967 | 0.4801 | 3.3678 | 3.603 | 19.0 | | 17.5532 | 33.64 | 21700 | 10.2384 | 2.6534 | 0.3239 | 2.3276 | 2.4692 | 19.0 | | 17.5532 | 33.8 | 21800 | 10.1929 | 2.6025 | 0.2845 | 2.2653 | 2.4507 | 19.0 | | 17.5532 | 33.95 | 21900 | 10.1016 | 3.3244 | 0.377 | 2.8311 | 3.0784 | 19.0 | | 17.3872 | 34.11 | 22000 | 10.1407 | 3.4245 | 0.4024 | 3.044 | 3.1865 | 19.0 | | 17.3872 | 34.26 | 22100 | 10.0760 | 3.9251 | 0.4272 | 3.4064 | 3.6497 | 19.0 | | 17.3872 | 34.42 | 22200 | 10.0998 | 3.3034 | 0.3438 | 2.8977 | 3.1141 | 19.0 | | 17.3872 | 34.57 | 22300 | 10.0834 | 2.4967 | 0.266 | 2.2301 | 2.3647 | 19.0 | | 17.3872 | 34.73 | 22400 | 9.9902 | 4.0828 | 0.4867 | 3.5482 | 3.7861 | 19.0 | | 17.1744 | 34.88 | 22500 | 10.0366 | 3.5772 | 0.4377 | 3.1153 | 3.3199 | 19.0 | | 17.1744 | 35.04 | 22600 | 10.0299 | 3.5342 | 0.433 | 3.0501 | 3.2176 | 19.0 | | 17.1744 | 35.19 | 22700 | 9.9912 | 3.7754 | 0.4445 | 3.3191 | 3.502 | 19.0 | | 17.1744 | 35.35 | 22800 | 9.9580 | 4.5086 | 0.5514 | 3.8986 | 4.1987 | 19.0 | | 17.1744 | 35.5 | 22900 | 9.9676 | 3.526 | 0.3942 | 3.0859 | 3.3082 | 19.0 | | 17.0687 | 35.66 | 23000 | 9.9874 | 3.7058 | 0.5139 | 3.2353 | 3.4611 | 19.0 | | 17.0687 | 35.81 | 23100 | 9.9536 | 3.6588 | 0.4552 | 3.1591 | 3.3554 | 19.0 | | 17.0687 | 35.97 | 23200 | 9.8948 | 3.6279 | 0.3933 | 3.1403 | 3.3426 | 19.0 | | 17.0687 | 36.12 | 23300 | 9.8397 | 3.8101 | 0.4971 | 3.3152 | 3.5133 | 19.0 | | 17.0687 | 36.28 | 23400 | 9.8995 | 3.3201 | 0.4209 | 2.9101 | 3.0903 | 19.0 | | 16.7686 | 36.43 | 23500 | 9.9085 | 4.0108 | 0.6389 | 3.5055 | 3.7286 | 19.0 | | 16.7686 | 36.59 | 23600 | 9.8688 | 3.6051 | 0.5164 | 3.1651 | 3.3781 | 19.0 | | 16.7686 | 36.74 | 23700 | 9.8673 | 4.4987 | 0.6051 | 3.8789 | 4.1868 | 19.0 | | 16.7686 | 36.9 | 23800 | 9.8848 | 3.6926 | 0.5635 | 3.1681 | 3.3902 | 19.0 | | 16.7686 | 37.05 | 23900 | 9.8497 | 3.518 | 0.4283 | 3.1159 | 3.3112 | 19.0 | | 16.7432 | 37.21 | 24000 | 9.8044 | 3.3369 | 0.3772 | 2.9784 | 3.147 | 19.0 | | 16.7432 | 37.36 | 24100 | 9.7768 | 3.5862 | 0.3819 | 3.1273 | 3.3535 | 19.0 | | 16.7432 | 37.52 | 24200 | 9.7536 | 4.1823 | 0.5884 | 3.645 | 3.8843 | 19.0 | | 16.7432 | 37.67 | 24300 | 9.7953 | 4.3981 | 0.6441 | 3.7941 | 4.0623 | 19.0 | | 16.7432 | 37.83 | 24400 | 9.6742 | 3.7833 | 0.4755 | 3.3516 | 3.5543 | 19.0 | | 16.5714 | 37.98 | 24500 | 9.7946 | 3.3839 | 0.495 | 3.0021 | 3.156 | 19.0 | | 16.5714 | 38.14 | 24600 | 9.7544 | 4.3873 | 0.6486 | 3.8188 | 4.0653 | 19.0 | | 16.5714 | 38.29 | 24700 | 9.7586 | 3.4403 | 0.4756 | 3.0402 | 3.2405 | 19.0 | | 16.5714 | 38.45 | 24800 | 9.7895 | 3.6822 | 0.6247 | 3.2612 | 3.4746 | 19.0 | | 16.5714 | 38.6 | 24900 | 9.6964 | 3.8743 | 0.6209 | 3.4159 | 3.6051 | 19.0 | | 16.3393 | 38.76 | 25000 | 9.7190 | 4.1508 | 0.635 | 3.5925 | 3.8753 | 19.0 | | 16.3393 | 38.91 | 25100 | 9.6435 | 3.6755 | 0.4777 | 3.268 | 3.4572 | 19.0 | | 16.3393 | 39.07 | 25200 | 9.6390 | 2.9478 | 0.4049 | 2.6531 | 2.7782 | 19.0 | | 16.3393 | 39.22 | 25300 | 9.6300 | 2.9973 | 0.3897 | 2.6662 | 2.7943 | 19.0 | | 16.3393 | 39.38 | 25400 | 9.6229 | 3.6726 | 0.4182 | 3.2207 | 3.4595 | 19.0 | | 16.3076 | 39.53 | 25500 | 9.6392 | 2.9691 | 0.3692 | 2.6709 | 2.8182 | 19.0 | | 16.3076 | 39.69 | 25600 | 9.5978 | 2.8167 | 0.3437 | 2.593 | 2.7155 | 19.0 | | 16.3076 | 39.84 | 25700 | 9.6111 | 3.5135 | 0.5453 | 3.1415 | 3.3042 | 19.0 | | 16.3076 | 40.0 | 25800 | 9.6118 | 3.459 | 0.4963 | 3.1351 | 3.2809 | 19.0 | | 16.3076 | 40.16 | 25900 | 9.5994 | 3.5735 | 0.539 | 3.2556 | 3.3904 | 19.0 | | 16.0684 | 40.31 | 26000 | 9.5526 | 3.3388 | 0.4689 | 2.9753 | 3.1562 | 19.0 | | 16.0684 | 40.47 | 26100 | 9.5365 | 3.0882 | 0.392 | 2.8072 | 2.9556 | 19.0 | | 16.0684 | 40.62 | 26200 | 9.5571 | 3.0022 | 0.4109 | 2.7108 | 2.8575 | 19.0 | | 16.0684 | 40.78 | 26300 | 9.5240 | 3.506 | 0.5734 | 3.1577 | 3.3378 | 19.0 | | 16.0684 | 40.93 | 26400 | 9.4913 | 3.5936 | 0.5165 | 3.2452 | 3.4134 | 19.0 | | 15.9425 | 41.09 | 26500 | 9.5297 | 3.7802 | 0.6862 | 3.4061 | 3.5436 | 19.0 | | 15.9425 | 41.24 | 26600 | 9.4657 | 3.8433 | 0.6105 | 3.4621 | 3.638 | 19.0 | | 15.9425 | 41.4 | 26700 | 9.5049 | 3.5822 | 0.6462 | 3.231 | 3.3745 | 19.0 | | 15.9425 | 41.55 | 26800 | 9.4739 | 2.9668 | 0.4426 | 2.7345 | 2.8134 | 19.0 | | 15.9425 | 41.71 | 26900 | 9.4868 | 3.7458 | 0.6934 | 3.3708 | 3.5492 | 19.0 | | 15.7779 | 41.86 | 27000 | 9.4683 | 3.5254 | 0.6006 | 3.1629 | 3.3011 | 19.0 | | 15.7779 | 42.02 | 27100 | 9.4108 | 4.2731 | 0.7412 | 3.8236 | 4.0171 | 19.0 | | 15.7779 | 42.17 | 27200 | 9.3994 | 3.5014 | 0.5738 | 3.1525 | 3.3306 | 19.0 | | 15.7779 | 42.33 | 27300 | 9.3760 | 3.4929 | 0.4954 | 3.1402 | 3.3028 | 19.0 | | 15.7779 | 42.48 | 27400 | 9.4201 | 4.2777 | 0.7152 | 3.7943 | 4.0349 | 19.0 | | 15.7238 | 42.64 | 27500 | 9.3913 | 3.6489 | 0.6371 | 3.2903 | 3.4528 | 19.0 | | 15.7238 | 42.79 | 27600 | 9.4269 | 3.5269 | 0.6042 | 3.2049 | 3.3528 | 19.0 | | 15.7238 | 42.95 | 27700 | 9.3847 | 3.4735 | 0.5963 | 3.1522 | 3.2796 | 19.0 | | 15.7238 | 43.1 | 27800 | 9.3474 | 3.8327 | 0.6428 | 3.406 | 3.5698 | 19.0 | | 15.7238 | 43.26 | 27900 | 9.3293 | 3.5475 | 0.6313 | 3.1725 | 3.3367 | 19.0 | | 15.5108 | 43.41 | 28000 | 9.3802 | 4.249 | 0.7997 | 3.7924 | 3.9849 | 19.0 | | 15.5108 | 43.57 | 28100 | 9.2588 | 3.4476 | 0.4676 | 3.1758 | 3.2993 | 19.0 | | 15.5108 | 43.72 | 28200 | 9.3447 | 4.0267 | 0.7081 | 3.6208 | 3.7957 | 19.0 | | 15.5108 | 43.88 | 28300 | 9.2853 | 4.0105 | 0.7799 | 3.5848 | 3.7619 | 19.0 | | 15.5108 | 44.03 | 28400 | 9.2753 | 3.1833 | 0.4678 | 2.9068 | 3.0168 | 19.0 | | 15.4004 | 44.19 | 28500 | 9.2345 | 3.6778 | 0.5955 | 3.3212 | 3.4724 | 19.0 | | 15.4004 | 44.34 | 28600 | 9.3130 | 3.9958 | 0.6892 | 3.5871 | 3.772 | 19.0 | | 15.4004 | 44.5 | 28700 | 9.2984 | 4.1868 | 0.696 | 3.7194 | 3.9197 | 19.0 | | 15.4004 | 44.65 | 28800 | 9.2722 | 3.8848 | 0.5914 | 3.5038 | 3.7022 | 19.0 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.12.0 - Datasets 2.3.2 - Tokenizers 0.12.1

jonatasgrosman/exp_w2v2t_it_wav2vec2_s211

jonatasgrosman

2022-07-08T18:47:36Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T18:46:52Z

--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_wav2vec2_s211 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_it_wav2vec2_s692

jonatasgrosman

2022-07-08T18:40:27Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T18:39:44Z

--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_wav2vec2_s692 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_vp-it_s621

jonatasgrosman

2022-07-08T18:34:01Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T18:33:37Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-it_s621 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_vp-it_s73

jonatasgrosman

2022-07-08T18:24:40Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T18:24:16Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-it_s73 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_r-wav2vec2_s303

jonatasgrosman

2022-07-08T18:20:50Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T18:20:08Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_r-wav2vec2_s303 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_r-wav2vec2_s201

jonatasgrosman

2022-07-08T18:16:03Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T18:15:40Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_r-wav2vec2_s201 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_r-wav2vec2_s911

jonatasgrosman

2022-07-08T18:12:55Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T18:12:33Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_r-wav2vec2_s911 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_xls-r_s42

jonatasgrosman

2022-07-08T18:06:10Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T18:05:28Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_xls-r_s42 Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_unispeech-sat_s635

jonatasgrosman

2022-07-08T17:58:13Z

4

0

transformers

[ "transformers", "pytorch", "unispeech-sat", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T17:57:49Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech-sat_s635 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

ndhieunguyen/ppo-SpaceInvadersNoFrameskip-v4

ndhieunguyen

2022-07-08T17:57:39Z

1

0

stable-baselines3

[ "stable-baselines3", "SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]

reinforcement-learning

2023-04-26T15:34:31Z

--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - metrics: - type: mean_reward value: 688.00 +/- 388.59 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 type: SpaceInvadersNoFrameskip-v4 --- # **DQN** Agent playing **SpaceInvadersNoFrameskip-v4** This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo SB3: https://github.com/DLR-RM/stable-baselines3 SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib ``` # Download model and save it into the logs/ folder python -m utils.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga infinitejoy -f logs/ python enjoy.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` ## Training (with the RL Zoo) ``` python train.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ # Upload the model and generate video (when possible) python -m utils.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga infinitejoy ``` ## Hyperparameters ```python OrderedDict([('batch_size', 32), ('buffer_size', 100000), ('env_wrapper', ['stable_baselines3.common.atari_wrappers.AtariWrapper']), ('exploration_final_eps', 0.01), ('exploration_fraction', 0.1), ('frame_stack', 4), ('gradient_steps', 1), ('learning_rate', 0.0001), ('learning_starts', 100000), ('n_timesteps', 10000000.0), ('optimize_memory_usage', True), ('policy', 'CnnPolicy'), ('target_update_interval', 1000), ('train_freq', 4), ('normalize', False)]) ```

jonatasgrosman/exp_w2v2t_ja_unispeech-sat_s884

jonatasgrosman

2022-07-08T17:51:35Z

5

0

transformers

[ "transformers", "pytorch", "unispeech-sat", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T17:51:10Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech-sat_s884 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_vp-nl_s770

jonatasgrosman

2022-07-08T17:48:07Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T17:47:43Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-nl_s770 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_vp-nl_s287

jonatasgrosman

2022-07-08T17:44:15Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T17:43:51Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-nl_s287 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_vp-nl_s682

jonatasgrosman

2022-07-08T17:41:08Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T17:40:45Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-nl_s682 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_vp-es_s673

jonatasgrosman

2022-07-08T17:33:40Z

7

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T17:33:01Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-es_s673 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_vp-fr_s543

jonatasgrosman

2022-07-08T17:26:45Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T17:26:03Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-fr_s543 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_vp-fr_s458

jonatasgrosman

2022-07-08T17:22:44Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T17:22:19Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-fr_s458 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_vp-fr_s368

jonatasgrosman

2022-07-08T17:18:18Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T17:17:49Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-fr_s368 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

infinitejoy/dqn-SpaceInvadersNoFrameskip-v4

infinitejoy

2022-07-08T17:14:02Z

3

0

stable-baselines3

[ "stable-baselines3", "SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]

reinforcement-learning

2022-07-08T17:05:23Z

--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - metrics: - type: mean_reward value: 688.00 +/- 388.59 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 type: SpaceInvadersNoFrameskip-v4 --- # **DQN** Agent playing **SpaceInvadersNoFrameskip-v4** This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo SB3: https://github.com/DLR-RM/stable-baselines3 SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib ``` # Download model and save it into the logs/ folder python -m utils.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga infinitejoy -f logs/ python enjoy.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` ## Training (with the RL Zoo) ``` python train.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ # Upload the model and generate video (when possible) python -m utils.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga infinitejoy ``` ## Hyperparameters ```python OrderedDict([('batch_size', 32), ('buffer_size', 100000), ('env_wrapper', ['stable_baselines3.common.atari_wrappers.AtariWrapper']), ('exploration_final_eps', 0.01), ('exploration_fraction', 0.1), ('frame_stack', 4), ('gradient_steps', 1), ('learning_rate', 0.0001), ('learning_starts', 100000), ('n_timesteps', 10000000.0), ('optimize_memory_usage', True), ('policy', 'CnnPolicy'), ('target_update_interval', 1000), ('train_freq', 4), ('normalize', False)]) ```

jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s886

jonatasgrosman

2022-07-08T17:06:46Z

5

0

transformers

[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T17:06:23Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech-ml_s886 Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_wavlm_s664

jonatasgrosman

2022-07-08T17:03:01Z

6

1

transformers

[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T17:02:32Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_wavlm_s664 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_vp-sv_s570

jonatasgrosman

2022-07-08T16:43:15Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T16:42:50Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_vp-sv_s570 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

Nitika/distilbert-base-uncased-finetuned-squad-d5716d28

Nitika

2022-07-08T16:36:38Z

0

null

[ "pytorch", "question-answering", "en", "dataset:squad", "arxiv:1910.01108", "license:apache-2.0", "region:us" ]

question-answering

2022-07-08T16:36:27Z

--- language: - en thumbnail: https://github.com/karanchahal/distiller/blob/master/distiller.jpg tags: - question-answering license: apache-2.0 datasets: - squad metrics: - squad --- # DistilBERT with a second step of distillation ## Model description This model replicates the "DistilBERT (D)" model from Table 2 of the [DistilBERT paper](https://arxiv.org/pdf/1910.01108.pdf). In this approach, a DistilBERT student is fine-tuned on SQuAD v1.1, but with a BERT model (also fine-tuned on SQuAD v1.1) acting as a teacher for a second step of task-specific distillation. In this version, the following pre-trained models were used: * Student: `distilbert-base-uncased` * Teacher: `lewtun/bert-base-uncased-finetuned-squad-v1` ## Training data This model was trained on the SQuAD v1.1 dataset which can be obtained from the `datasets` library as follows: ```python from datasets import load_dataset squad = load_dataset('squad') ``` ## Training procedure ## Eval results | | Exact Match | F1 | |------------------|-------------|------| | DistilBERT paper | 79.1 | 86.9 | | Ours | 78.4 | 86.5 | The scores were calculated using the `squad` metric from `datasets`. ### BibTeX entry and citation info ```bibtex @misc{sanh2020distilbert, title={DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter}, author={Victor Sanh and Lysandre Debut and Julien Chaumond and Thomas Wolf}, year={2020}, eprint={1910.01108}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```

jonatasgrosman/exp_w2v2t_ja_hubert_s732

jonatasgrosman

2022-07-08T16:24:39Z

4

0

transformers

[ "transformers", "pytorch", "hubert", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T16:24:16Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_hubert_s732 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_unispeech_s947

jonatasgrosman

2022-07-08T16:21:33Z

4

0

transformers

[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T16:21:10Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech_s947 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_unispeech_s253

jonatasgrosman

2022-07-08T16:18:02Z

4

0

transformers

[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T16:17:38Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech_s253 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_unispeech_s569

jonatasgrosman

2022-07-08T16:14:48Z

3

0

transformers

[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T16:14:24Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_unispeech_s569 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_xlsr-53_s781

jonatasgrosman

2022-07-08T16:08:42Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T16:08:19Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_xlsr-53_s781 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_wav2vec2_s727

jonatasgrosman

2022-07-08T15:53:02Z

5

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T15:52:34Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_wav2vec2_s727 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_wav2vec2_s895

jonatasgrosman

2022-07-08T15:49:30Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T15:49:04Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_wav2vec2_s895 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_ja_wav2vec2_s834

jonatasgrosman

2022-07-08T15:46:20Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "ja", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T15:45:39Z

--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - ja datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_ja_wav2vec2_s834 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (ja)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

Rocketknight1/bert-dummy-seq

Rocketknight1

2022-07-08T15:45:02Z

3

0

transformers

[ "transformers", "tf", "bert", "text-classification", "generated_from_keras_callback", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2022-07-08T15:18:33Z

--- license: apache-2.0 tags: - generated_from_keras_callback model-index: - name: bert-dummy-seq results: [] ---  # bert-dummy-seq This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. It achieves the following results on the evaluation set: ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: None - training_precision: float32 ### Training results ### Framework versions - Transformers 4.21.0.dev0 - TensorFlow 2.9.1 - Datasets 2.3.3.dev0 - Tokenizers 0.11.0

jonatasgrosman/exp_w2v2t_th_vp-it_s819

jonatasgrosman

2022-07-08T15:31:43Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T15:31:17Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-it_s819 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_vp-it_s259

jonatasgrosman

2022-07-08T15:28:35Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T15:28:09Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-it_s259 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

tfshaman/distilbert-base-uncased-distilled-clinc

tfshaman

2022-07-08T15:19:17Z

10

0

transformers

[ "transformers", "pytorch", "distilbert", "text-classification", "generated_from_trainer", "dataset:clinc_oos", "license:apache-2.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2022-07-08T14:52:51Z

--- license: apache-2.0 tags: - generated_from_trainer datasets: - clinc_oos metrics: - accuracy model-index: - name: distilbert-base-uncased-distilled-clinc results: - task: name: Text Classification type: text-classification dataset: name: clinc_oos type: clinc_oos args: plus metrics: - name: Accuracy type: accuracy value: 0.8264516129032258 ---  # distilbert-base-uncased-distilled-clinc This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset. It achieves the following results on the evaluation set: - Loss: 1.5565 - Accuracy: 0.8265 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 3.2743 | 1.0 | 318 | 2.5809 | 0.7310 | | 2.2148 | 2.0 | 636 | 1.7909 | 0.8071 | | 1.7065 | 3.0 | 954 | 1.5565 | 0.8265 | ### Framework versions - Transformers 4.21.0.dev0 - Pytorch 1.12.0 - Datasets 2.3.2 - Tokenizers 0.12.1

jonatasgrosman/exp_w2v2t_th_r-wav2vec2_s805

jonatasgrosman

2022-07-08T15:18:14Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T15:17:48Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_r-wav2vec2_s805 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_xls-r_s590

jonatasgrosman

2022-07-08T15:14:52Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T15:14:26Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_xls-r_s590 Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_xls-r_s879

jonatasgrosman

2022-07-08T15:11:46Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T15:11:20Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_xls-r_s879 Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_xls-r_s625

jonatasgrosman

2022-07-08T15:07:51Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T15:07:26Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_xls-r_s625 Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

dminiotas05/distilbert-base-uncased-finetuned-ft650_10class

dminiotas05

2022-07-08T14:58:07Z

5

0

transformers

[ "transformers", "pytorch", "tensorboard", "distilbert", "text-classification", "generated_from_trainer", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2022-07-08T14:33:27Z

--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-ft650_10class results: [] ---  # distilbert-base-uncased-finetuned-ft650_10class This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.9674 - Accuracy: 0.2207 - F1: 0.2002 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 2.1088 | 1.0 | 188 | 2.0460 | 0.1807 | 0.1324 | | 1.9628 | 2.0 | 376 | 1.9867 | 0.2173 | 0.1821 | | 1.8966 | 3.0 | 564 | 1.9693 | 0.2193 | 0.1936 | | 1.8399 | 4.0 | 752 | 1.9674 | 0.2207 | 0.2002 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1

jonatasgrosman/exp_w2v2t_th_unispeech-sat_s658

jonatasgrosman

2022-07-08T14:57:17Z

4

0

transformers

[ "transformers", "pytorch", "unispeech-sat", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T14:56:29Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_unispeech-sat_s658 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_vp-nl_s947

jonatasgrosman

2022-07-08T14:53:03Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T14:52:36Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-nl_s947 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

micheljperez/dqn-SpaceInvadersNoFrameskip-v4-2

micheljperez

2022-07-08T14:47:15Z

2

0

stable-baselines3

[ "stable-baselines3", "SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]

reinforcement-learning

2022-07-05T13:17:28Z

--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - metrics: - type: mean_reward value: 1092.00 +/- 250.80 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 type: SpaceInvadersNoFrameskip-v4 --- # **DQN** Agent playing **SpaceInvadersNoFrameskip-v4** This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo SB3: https://github.com/DLR-RM/stable-baselines3 SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib ``` # Download model and save it into the logs/ folder python -m utils.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga micheljperez -f logs/ python enjoy.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` ## Training (with the RL Zoo) ``` python train.py --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ # Upload the model and generate video (when possible) python -m utils.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga micheljperez ``` ## Hyperparameters ```python OrderedDict([('batch_size', 32), ('buffer_size', 100000), ('env_wrapper', ['stable_baselines3.common.atari_wrappers.AtariWrapper']), ('exploration_final_eps', 0.01), ('exploration_fraction', 0.07817), ('frame_stack', 4), ('gradient_steps', 1), ('learning_rate', 0.3571), ('learning_starts', 100000), ('n_timesteps', 10000000), ('optimize_memory_usage', True), ('policy', 'CnnPolicy'), ('target_update_interval', 1000), ('train_freq', 4), ('normalize', False)]) ```

Zengwei/icefall-asr-librispeech-conv-emformer-transducer-stateless2-larger-latency-2022-07-06

Zengwei

2022-07-08T14:40:32Z

0

null

[ "tensorboard", "region:us" ]

null

2022-07-06T08:44:45Z

# Introduction See https://github.com/k2-fsa/icefall/pull/440 This model use the following setup: * length of chunk is 64 frames (i.e., 0.64s) * length of right context is 16 frames (i.e., 0.16s)

Nonzerophilip/bert-finetuned-ner_swedish_small_set_health_and_prices

Nonzerophilip

2022-07-08T14:01:49Z

4

0

transformers

[ "transformers", "pytorch", "tensorboard", "bert", "token-classification", "generated_from_trainer", "autotrain_compatible", "endpoints_compatible", "region:us" ]

token-classification

2022-07-08T10:53:18Z

--- tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: bert-finetuned-ner_swedish_small_set_health_and_prices results: [] ---  # bert-finetuned-ner_swedish_small_set_health_and_prices This model is a fine-tuned version of [KBLab/bert-base-swedish-cased-ner](https://huggingface.co/KBLab/bert-base-swedish-cased-ner) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0942 - Precision: 0.7709 - Recall: 0.8118 - F1: 0.7908 - Accuracy: 0.9741 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 250 | 0.1310 | 0.6116 | 0.7471 | 0.6726 | 0.9578 | | 0.1583 | 2.0 | 500 | 0.0939 | 0.7560 | 0.8020 | 0.7783 | 0.9737 | | 0.1583 | 3.0 | 750 | 0.0942 | 0.7709 | 0.8118 | 0.7908 | 0.9741 | ### Framework versions - Transformers 4.19.3 - Pytorch 1.7.1 - Datasets 2.2.2 - Tokenizers 0.12.1

malteos/gpt2-xl-german-covid-19

malteos

2022-07-08T13:48:32Z

7

0

transformers

[ "transformers", "pytorch", "gpt2", "text-generation", "de", "license:mit", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2022-07-08T13:14:23Z

--- license: mit language: de widget: - text: "Noch Wochen nach einer Erkrankung an COVID-19 können " --- # German Covid-19 GPT2-XL (1.5B) - Covid-19 specific version of [`malteos/gpt2-xl-wechsel-german`](https://huggingface.co/malteos/gpt2-xl-wechsel-german) - Fine-tuned on 2 GB text from OSCAR filtered for covid related terms. ### How to use You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we set a seed for reproducibility: ```python >>> from transformers import pipeline, set_seed >>> generator = pipeline('text-generation', model='malteos/gpt2-xl-german-covid-19') >>> set_seed(42) >>> generator("Hello, I'm a language model,", max_length=30, num_return_sequences=5) ``` ## License MIT

jonatasgrosman/exp_w2v2t_th_vp-es_s26

jonatasgrosman

2022-07-08T13:44:23Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T12:25:24Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-es_s26 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

Guillaume63/Reinforce-cartpole

Guillaume63

2022-07-08T13:06:18Z

0

null

[ "CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class", "model-index", "region:us" ]

reinforcement-learning

2022-07-06T12:59:13Z

--- tags: - CartPole-v1 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinforce-cartpole results: - metrics: - type: mean_reward value: 500.00 +/- 0.00 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 --- # **Reinforce** Agent playing **CartPole-v1** This is a trained model of a **Reinforce** agent playing **CartPole-v1** . To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit5

ramonzaca/testpyramidsrnd

ramonzaca

2022-07-08T12:16:14Z

11

0

ml-agents

[ "ml-agents", "tensorboard", "onnx", "unity-ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids", "region:us" ]

reinforcement-learning

2022-07-08T12:16:09Z

--- tags: - unity-ml-agents - ml-agents - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Pyramids library_name: ml-agents --- # **ppo** Agent playing **Pyramids** This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://github.com/huggingface/ml-agents#get-started We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: ### Resume the training ``` mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent **playing directly in your browser:**. 1. Go to https://huggingface.co/spaces/unity/ML-Agents-Pyramids 2. Step 1: Write your model_id: ramonzaca/testpyramidsrnd 3. Step 2: Select your *.nn /*.onnx file 4. Click on Watch the agent play 👀

dminiotas05/distilbert-base-uncased-finetuned-ft650_6class

dminiotas05

2022-07-08T12:11:05Z

3

0

transformers

[ "transformers", "pytorch", "tensorboard", "distilbert", "text-classification", "generated_from_trainer", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2022-07-08T11:46:36Z

--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-ft650_6class results: [] ---  # distilbert-base-uncased-finetuned-ft650_6class This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.4555 - Accuracy: 0.3707 - F1: 0.3625 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 1.5838 | 1.0 | 188 | 1.5235 | 0.3253 | 0.2947 | | 1.4521 | 2.0 | 376 | 1.4744 | 0.3467 | 0.3234 | | 1.3838 | 3.0 | 564 | 1.4565 | 0.358 | 0.3483 | | 1.323 | 4.0 | 752 | 1.4555 | 0.3707 | 0.3625 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1

jourlin/wiki2json

jourlin

2022-07-08T11:46:44Z

6

0

transformers

[ "transformers", "pytorch", "t5", "text2text-generation", "generated_from_trainer", "dataset:opus_books", "license:apache-2.0", "model-index", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text2text-generation

2022-07-08T06:58:40Z

--- license: apache-2.0 tags: - generated_from_trainer datasets: - opus_books metrics: - bleu model-index: - name: wiki2json results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: opus_books type: opus_books args: en-fr metrics: - name: Bleu type: bleu value: 4.8968 ---  # wiki2json This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the opus_books dataset. It achieves the following results on the evaluation set: - Loss: 1.6848 - Bleu: 4.8968 - Gen Len: 17.6362 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:| | 1.9187 | 1.0 | 3178 | 1.6848 | 4.8968 | 17.6362 | ### Framework versions - Transformers 4.18.0 - Pytorch 1.10.2+cu102 - Datasets 2.3.2 - Tokenizers 0.12.1

jonatasgrosman/exp_w2v2t_th_unispeech-ml_s256

jonatasgrosman

2022-07-08T11:28:09Z

3

0

transformers

[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T11:27:41Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_unispeech-ml_s256 Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_wavlm_s904

jonatasgrosman

2022-07-08T11:25:12Z

5

0

transformers

[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T11:23:56Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_wavlm_s904 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_wavlm_s847

jonatasgrosman

2022-07-08T11:21:22Z

4

0

transformers

[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T11:20:15Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_wavlm_s847 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_vp-sv_s884

jonatasgrosman

2022-07-08T11:04:20Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T11:03:49Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-sv_s884 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_vp-sv_s635

jonatasgrosman

2022-07-08T11:01:14Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T11:00:49Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-sv_s635 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_vp-sv_s946

jonatasgrosman

2022-07-08T10:58:13Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T10:57:48Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-sv_s946 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_hubert_s533

jonatasgrosman

2022-07-08T10:52:20Z

4

0

transformers

[ "transformers", "pytorch", "hubert", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T10:51:52Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_hubert_s533 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_unispeech_s131

jonatasgrosman

2022-07-08T10:45:46Z

3

0

transformers

[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T10:45:06Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_unispeech_s131 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_unispeech_s328

jonatasgrosman

2022-07-08T10:39:17Z

4

0

transformers

[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T10:38:31Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_unispeech_s328 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_xlsr-53_s201

jonatasgrosman

2022-07-08T10:31:19Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T10:30:49Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_xlsr-53_s201 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_xlsr-53_s711

jonatasgrosman

2022-07-08T10:27:24Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T10:26:54Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_xlsr-53_s711 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_vp-100k_s630

jonatasgrosman

2022-07-08T10:24:25Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T10:23:54Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-100k_s630 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_vp-100k_s497

jonatasgrosman

2022-07-08T10:21:24Z

5

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T10:20:58Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_vp-100k_s497 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_th_wav2vec2_s664

jonatasgrosman

2022-07-08T10:06:53Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "th", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T10:06:28Z

--- language: - th license: apache-2.0 tags: - automatic-speech-recognition - th datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_th_wav2vec2_s664 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

swtx/ernie-gram-chinese

swtx

2022-07-08T09:44:33Z

5

0

transformers

[ "transformers", "pytorch", "bert", "feature-extraction", "arxiv:2010.12148", "endpoints_compatible", "region:us" ]

feature-extraction

2022-07-08T09:09:46Z

--- language: chinese --- # ERNIE-Gram-chinese ## Introduction ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding More detail: https://arxiv.org/abs/2010.12148 ## Released Model Info |Model Name|Language|Model Structure| |:---:|:---:|:---:| |ernie-gram-chinese| Chinese |Layer:12, Hidden:768, Heads:12| This released Pytorch model is converted from the officially released PaddlePaddle ERNIE model and a series of experiments have been conducted to check the accuracy of the conversion. - Official PaddlePaddle ERNIE repo: https://github.com/PaddlePaddle/ERNIE - Pytorch Conversion repo: https://github.com/nghuyong/ERNIE-Pytorch ## How to use ```Python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("swtx/ernie-gram-chinese") model = AutoModel.from_pretrained("swtx/ernie-gram-chinese") ```

jonatasgrosman/exp_w2v2t_en_r-wav2vec2_s44

jonatasgrosman

2022-07-08T09:36:19Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T09:35:33Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_r-wav2vec2_s44 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_r-wav2vec2_s93

jonatasgrosman

2022-07-08T09:28:53Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T09:28:09Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_r-wav2vec2_s93 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

epsil/testpyramidsrnd

epsil

2022-07-08T09:27:21Z

4

0

ml-agents

[ "ml-agents", "tensorboard", "onnx", "unity-ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids", "region:us" ]

reinforcement-learning

2022-07-08T09:27:16Z

--- tags: - unity-ml-agents - ml-agents - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Pyramids library_name: ml-agents --- # **ppo** Agent playing **Pyramids** This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://github.com/huggingface/ml-agents#get-started We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: ### Resume the training ``` mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent **playing directly in your browser:**. 1. Go to https://huggingface.co/spaces/unity/ML-Agents-Pyramids 2. Step 1: Write your model_id: epsil/testpyramidsrnd 3. Step 2: Select your *.nn /*.onnx file 4. Click on Watch the agent play 👀

jonatasgrosman/exp_w2v2t_en_r-wav2vec2_s863

jonatasgrosman

2022-07-08T09:19:20Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T09:18:31Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_r-wav2vec2_s863 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459

jonatasgrosman

2022-07-08T08:46:57Z

5

0

transformers

[ "transformers", "pytorch", "unispeech-sat", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T08:46:09Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_unispeech-sat_s459 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_unispeech-sat_s456

jonatasgrosman

2022-07-08T08:26:50Z

6

0

transformers

[ "transformers", "pytorch", "unispeech-sat", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T08:26:01Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_unispeech-sat_s456 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

Shenghao1993/distilbert-base-uncased-finetuned-clinc

Shenghao1993

2022-07-08T08:22:36Z

23

0

transformers

[ "transformers", "pytorch", "tensorboard", "distilbert", "text-classification", "generated_from_trainer", "dataset:clinc_oos", "license:apache-2.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2022-07-06T15:20:11Z

--- license: apache-2.0 tags: - generated_from_trainer datasets: - clinc_oos metrics: - accuracy model-index: - name: distilbert-base-uncased-finetuned-clinc results: - task: name: Text Classification type: text-classification dataset: name: clinc_oos type: clinc_oos args: plus metrics: - name: Accuracy type: accuracy value: 0.9174193548387096 ---  # distilbert-base-uncased-finetuned-clinc This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset. It achieves the following results on the evaluation set: - Loss: 0.7711 - Accuracy: 0.9174 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 318 | 3.2830 | 0.7426 | | 3.785 | 2.0 | 636 | 1.8728 | 0.8410 | | 3.785 | 3.0 | 954 | 1.1555 | 0.8913 | | 1.6902 | 4.0 | 1272 | 0.8530 | 0.9126 | | 0.901 | 5.0 | 1590 | 0.7711 | 0.9174 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1

jonatasgrosman/exp_w2v2t_en_vp-nl_s281

jonatasgrosman

2022-07-08T08:09:32Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T08:08:43Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-nl_s281 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_vp-es_s186

jonatasgrosman

2022-07-08T07:54:17Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T07:53:28Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-es_s186 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_vp-es_s474

jonatasgrosman

2022-07-08T07:45:27Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T07:44:40Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-es_s474 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

ClassCat/roberta-base-french

ClassCat

2022-07-08T07:34:58Z

7

1

transformers

[ "transformers", "pytorch", "roberta", "fill-mask", "fr", "dataset:wikipedia", "dataset:cc100", "license:cc-by-sa-4.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

fill-mask

2022-07-04T17:58:21Z

--- language: fr license: cc-by-sa-4.0 datasets: - wikipedia - cc100 widget: - text: "Je vais à la <mask>." - text: "J'aime le <mask>." - text: "J'ai ouvert la <mask>." - text: "Je m'appelle <mask>." - text: "J'ai beaucoup d'<mask>." --- ## RoBERTa French base model (Uncased) ### Prerequisites transformers==4.19.2 ### Model architecture This model uses RoBERTa base setttings except vocabulary size. ### Tokenizer Using BPE tokenizer with vocabulary size 50,000. ### Training Data * [wiki40b/fr](https://www.tensorflow.org/datasets/catalog/wiki40b#wiki40bfr) (French Wikipedia) * Subset of [CC-100/fr](https://data.statmt.org/cc-100/) : Monolingual Datasets from Web Crawl Data ### Usage ```python from transformers import pipeline unmasker = pipeline('fill-mask', model='ClassCat/roberta-base-french') unmasker("Je vais à la <mask>.") ```

jonatasgrosman/exp_w2v2t_en_vp-fr_s691

jonatasgrosman

2022-07-08T07:20:48Z

5

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T07:20:01Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-fr_s691 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_unispeech-ml_s377

jonatasgrosman

2022-07-08T06:52:52Z

3

0

transformers

[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T06:52:07Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_unispeech-ml_s377 Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_wavlm_s990

jonatasgrosman

2022-07-08T06:48:30Z

4

0

transformers

[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T06:47:43Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_wavlm_s990 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_wavlm_s461

jonatasgrosman

2022-07-08T06:40:13Z

5

0

transformers

[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T06:39:25Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_wavlm_s461 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_wavlm_s767

jonatasgrosman

2022-07-08T06:33:36Z

3

0

transformers

[ "transformers", "pytorch", "wavlm", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T06:32:43Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_wavlm_s767 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_no-pretraining_s883

jonatasgrosman

2022-07-08T06:16:41Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T06:16:14Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_no-pretraining_s883 Fine-tuned randomly initialized wav2vec2 model for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_vp-sv_s438

jonatasgrosman

2022-07-08T06:11:38Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T06:11:10Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-sv_s438 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_hubert_s875

jonatasgrosman

2022-07-08T05:46:21Z

3

0

transformers

[ "transformers", "pytorch", "hubert", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T05:45:44Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_hubert_s875 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_unispeech_s227

jonatasgrosman

2022-07-08T05:36:00Z

4

0

transformers

[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T05:35:18Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_unispeech_s227 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

phyous/q-Taxi-v3-2

phyous

2022-07-08T05:32:54Z

0

null

[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]

reinforcement-learning

2022-07-08T05:27:28Z

--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-Taxi-v3-2 results: - metrics: - type: mean_reward value: 7.56 +/- 2.71 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 --- # **Q-Learning** Agent playing **Taxi-v3** This is a trained model of a **Q-Learning** agent playing **Taxi-v3** . ## Usage ```python model = load_from_hub(repo_id="phyous/q-Taxi-v3-2", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) evaluate_agent(env, model["max_steps"], model["n_eval_episodes"], model["qtable"], model["eval_seed"]) ```

jonatasgrosman/exp_w2v2t_en_unispeech_s870

jonatasgrosman

2022-07-08T05:31:32Z

4

0

transformers

[ "transformers", "pytorch", "unispeech", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T05:30:42Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_unispeech_s870 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

phyous/q-Taxi-v3

phyous

2022-07-08T05:12:47Z

0

null

[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]

reinforcement-learning

2022-07-08T05:12:07Z

--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-Taxi-v3 results: - metrics: - type: mean_reward value: 7.44 +/- 2.74 name: mean_reward task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 --- # **Q-Learning** Agent playing **Taxi-v3** This is a trained model of a **Q-Learning** agent playing **Taxi-v3** . ## Usage ```python model = load_from_hub(repo_id="phyous/q-Taxi-v3", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) evaluate_agent(env, model["max_steps"], model["n_eval_episodes"], model["qtable"], model["eval_seed"]) ```

jonatasgrosman/exp_w2v2t_en_xlsr-53_s870

jonatasgrosman

2022-07-08T05:07:22Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T05:06:55Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_xlsr-53_s870 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

ChauNguyen23/phobert-base-finetuned-imdb

ChauNguyen23

2022-07-08T05:03:20Z

4

0

transformers

[ "transformers", "pytorch", "tensorboard", "roberta", "fill-mask", "generated_from_trainer", "dataset:imdb", "autotrain_compatible", "endpoints_compatible", "region:us" ]

fill-mask

2022-07-08T04:47:50Z

--- tags: - generated_from_trainer datasets: - imdb model-index: - name: phobert-base-finetuned-imdb results: [] ---  # phobert-base-finetuned-imdb This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the imdb dataset. It achieves the following results on the evaluation set: - Loss: 2.6149 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 3.3266 | 1.0 | 157 | 2.7949 | | 2.9162 | 2.0 | 314 | 2.6515 | | 2.8177 | 3.0 | 471 | 2.6452 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1

jonatasgrosman/exp_w2v2t_en_vp-100k_s364

jonatasgrosman

2022-07-08T04:56:51Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T04:56:25Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_vp-100k_s364 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

rserenity/shuukobot

rserenity

2022-07-08T04:38:26Z

0

null

[ "tensorboard", "text-generation", "region:us" ]

text-generation

2022-07-08T02:58:22Z

--- tags: - text-generation ---

jonatasgrosman/exp_w2v2t_en_wav2vec2_s203

jonatasgrosman

2022-07-08T04:24:19Z

3

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T04:23:34Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_wav2vec2_s203 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

jonatasgrosman/exp_w2v2t_en_wav2vec2_s924

jonatasgrosman

2022-07-08T04:12:02Z

4

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2022-07-08T03:56:41Z

--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_en_wav2vec2_s924 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.

okho0653/Bio_ClinicalBERT-zero-shot-tokenizer-truncation-sentiment-model

okho0653

2022-07-08T03:54:48Z

6

0

transformers

[ "transformers", "pytorch", "tensorboard", "bert", "text-classification", "generated_from_trainer", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2022-07-08T01:09:10Z

--- license: mit tags: - generated_from_trainer model-index: - name: Bio_ClinicalBERT-zero-shot-tokenizer-truncation-sentiment-model results: [] ---  # Bio_ClinicalBERT-zero-shot-tokenizer-truncation-sentiment-model This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1