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/
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jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-5_female-5_s621
5560a12b8018150fcf1747af564597c32e335e1c
2022-07-25T16:34:52.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-5_female-5_s621
1
null
transformers
33,400
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-5_female-5_s621 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 (en)](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_w2v2r_en_xls-r_gender_male-5_female-5_s73
e90dcea93b5e8461bad59b54c78c3c1225c7029d
2022-07-25T16:39:30.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-5_female-5_s73
1
null
transformers
33,401
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-5_female-5_s73 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 (en)](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_w2v2r_en_xls-r_gender_male-0_female-10_s727
defa3687a30074b0a29c17cd38e7deb6bb95c6d5
2022-07-25T16:44:02.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-0_female-10_s727
1
null
transformers
33,402
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-0_female-10_s727 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 (en)](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_w2v2r_en_xls-r_gender_male-0_female-10_s834
61612858f87cddd5478953b55e69c13bd0379257
2022-07-25T16:48:46.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-0_female-10_s834
1
null
transformers
33,403
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-0_female-10_s834 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 (en)](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_w2v2r_en_xls-r_gender_male-0_female-10_s895
bdacad97de611b27cbab011bf873c1a375914270
2022-07-25T16:54:07.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-0_female-10_s895
1
null
transformers
33,404
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-0_female-10_s895 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 (en)](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_w2v2r_en_xls-r_gender_male-10_female-0_s287
bf6882784927ccfa455f4fc0f7d6ab127061f4cb
2022-07-25T16:59:02.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-10_female-0_s287
1
null
transformers
33,405
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-10_female-0_s287 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 (en)](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_w2v2r_en_xls-r_gender_male-10_female-0_s682
1091641ad16638cc8f55510dab0e8d95976b3887
2022-07-25T17:03:49.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-10_female-0_s682
1
null
transformers
33,406
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-10_female-0_s682 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 (en)](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_w2v2r_en_xls-r_gender_male-10_female-0_s770
173c509f306f118949d766188a029af1a950ac65
2022-07-25T17:08:26.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-10_female-0_s770
1
null
transformers
33,407
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-10_female-0_s770 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 (en)](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_w2v2r_en_xls-r_gender_male-2_female-8_s201
db90760c563c8ee9f5b9e896c9f28b7acf89f6bf
2022-07-25T17:13:02.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-2_female-8_s201
1
null
transformers
33,408
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-2_female-8_s201 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 (en)](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_w2v2r_en_xls-r_gender_male-2_female-8_s303
bfeb624426f79d4ff92364ec454b51258c782b18
2022-07-25T17:17:54.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-2_female-8_s303
1
null
transformers
33,409
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-2_female-8_s303 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 (en)](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_w2v2r_en_xls-r_gender_male-2_female-8_s911
57fbab6bc1411622af6e16aa1a0a61d07127e3a9
2022-07-25T17:22:25.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-2_female-8_s911
1
null
transformers
33,410
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-2_female-8_s911 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 (en)](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_w2v2r_en_xls-r_gender_male-8_female-2_s26
57195b800d8ddbee91b9c07df9b9530ae796065c
2022-07-25T17:27:22.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-8_female-2_s26
1
null
transformers
33,411
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-8_female-2_s26 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 (en)](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_w2v2r_en_xls-r_gender_male-8_female-2_s322
04b5c8bbba0b57e8bf056b5571b2eadf53249568
2022-07-25T17:32:14.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-8_female-2_s322
1
null
transformers
33,412
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-8_female-2_s322 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 (en)](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_w2v2r_en_xls-r_gender_male-8_female-2_s570
5cabdd2b7124839f2b93c8840a3eb30e340343c1
2022-07-25T17:37:00.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "en", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-8_female-2_s570
1
null
transformers
33,413
--- language: - en license: apache-2.0 tags: - automatic-speech-recognition - en datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_en_xls-r_gender_male-8_female-2_s570 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 (en)](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_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s240
fa52a3c1984ac8ed2536a8856d29be371d9ecc51
2022-07-25T17:42:12.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s240
1
null
transformers
33,414
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s240 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s362
e9303cc2416051c1ea3484077649dc5952d2bcb3
2022-07-25T17:47:23.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s362
1
null
transformers
33,415
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s362 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s463
3bcce7028c49b8a56228090b6ae785292cf9bb10
2022-07-25T17:52:19.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s463
1
null
transformers
33,416
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-5_nortepeninsular-5_s463 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-0_nortepeninsular-10_s157
b11e90494c2141925aa1a61fab0d242affc7ae88
2022-07-25T17:57:25.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-0_nortepeninsular-10_s157
1
null
transformers
33,417
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-0_nortepeninsular-10_s157 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-0_nortepeninsular-10_s265
100573155c5e2750b1db793149fbd3d79a26db24
2022-07-25T18:02:01.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-0_nortepeninsular-10_s265
1
null
transformers
33,418
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-0_nortepeninsular-10_s265 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-0_nortepeninsular-10_s888
2079d073fa27971d665d88ab9488f494da5e2cb9
2022-07-25T18:07:03.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-0_nortepeninsular-10_s888
1
null
transformers
33,419
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-0_nortepeninsular-10_s888 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-10_nortepeninsular-0_s61
e52c511d85cd6aa167ecfb2718966a24c558b443
2022-07-25T18:12:28.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-10_nortepeninsular-0_s61
1
null
transformers
33,420
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-10_nortepeninsular-0_s61 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-10_nortepeninsular-0_s632
1ea5945ebfa7c68ee4200dec275ec3683fc3ea30
2022-07-25T18:17:53.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-10_nortepeninsular-0_s632
1
null
transformers
33,421
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-10_nortepeninsular-0_s632 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-10_nortepeninsular-0_s885
5aa5f342a9d12ef10a2bfd8263ebea31bd3a77ab
2022-07-25T18:22:30.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-10_nortepeninsular-0_s885
1
null
transformers
33,422
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-10_nortepeninsular-0_s885 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-2_nortepeninsular-8_s443
3d70df3634442c6f2bec88fb09fa96e718bbba7d
2022-07-25T18:27:20.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-2_nortepeninsular-8_s443
1
null
transformers
33,423
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-2_nortepeninsular-8_s443 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-2_nortepeninsular-8_s598
64ad70b8064cf1846474c01c144e5903f7d0e58e
2022-07-25T18:32:09.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-2_nortepeninsular-8_s598
1
null
transformers
33,424
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-2_nortepeninsular-8_s598 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 (es)](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.
naem1023/kcelectra-phrase-clause-classification-aug-personal
773f5d4f0852c94f9679911a69c4416715a203bf
2022-07-25T23:55:45.000Z
[ "pytorch", "electra", "text-classification", "transformers", "license:apache-2.0" ]
text-classification
false
naem1023
null
naem1023/kcelectra-phrase-clause-classification-aug-personal
1
null
transformers
33,425
--- license: apache-2.0 ---
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-2_nortepeninsular-8_s82
78e4d42aabcefeda26db034f80ceab99e65fdbcd
2022-07-25T18:38:39.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-2_nortepeninsular-8_s82
1
null
transformers
33,426
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-2_nortepeninsular-8_s82 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s187
e77834f85bbff179328b1966814a0fdd05d256e9
2022-07-25T18:43:16.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s187
1
null
transformers
33,427
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s187 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s507
26067d05227b68830ba44a8b2495319f5cbeb2b3
2022-07-25T18:48:16.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s507
1
null
transformers
33,428
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s507 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 (es)](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_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s571
379cd208ae1a270f8cc01e62ff5919b294ddcdbc
2022-07-25T18:53:20.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s571
1
null
transformers
33,429
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_accent_surpeninsular-8_nortepeninsular-2_s571 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 (es)](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.
ai4bharat/indicwav2vec_v1_gujarati
ce9630d2f0aa34940983515b28787d918470d130
2022-07-25T19:06:17.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "transformers" ]
automatic-speech-recognition
false
ai4bharat
null
ai4bharat/indicwav2vec_v1_gujarati
1
null
transformers
33,430
Entry not found
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-5_female-5_s263
ed5e874a2254b321f206042127e039e145c8daa2
2022-07-25T18:57:52.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-5_female-5_s263
1
null
transformers
33,431
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-5_female-5_s263 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 (es)](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.
ai4bharat/indicwav2vec_v1_bengali
d5fd90a4038c2d808b52ea20d68c281148158734
2022-07-25T19:02:42.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "transformers", "license:mit" ]
automatic-speech-recognition
false
ai4bharat
null
ai4bharat/indicwav2vec_v1_bengali
1
null
transformers
33,432
--- license: mit ---
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-5_female-5_s294
87da302adf21d01babc65215b1a0f5ba9d4952d4
2022-07-25T19:02:57.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-5_female-5_s294
1
null
transformers
33,433
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-5_female-5_s294 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 (es)](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_w2v2r_es_xls-r_gender_male-5_female-5_s932
72d6ecbd9389f8ba919cc50049fa466ff7c06d1d
2022-07-25T19:07:38.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-5_female-5_s932
1
null
transformers
33,434
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-5_female-5_s932 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 (es)](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_w2v2r_es_xls-r_gender_male-0_female-10_s695
fd98aadb05ee535a9933f5691957db14114832c1
2022-07-25T19:13:13.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-0_female-10_s695
1
null
transformers
33,435
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-0_female-10_s695 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 (es)](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_w2v2r_es_xls-r_gender_male-0_female-10_s951
469b0bc727076e139027a0795cfedb1459548fbd
2022-07-25T19:17:48.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-0_female-10_s951
1
null
transformers
33,436
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-0_female-10_s951 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 (es)](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_w2v2r_es_xls-r_gender_male-0_female-10_s961
34bd2f5a6456e8fd8c617a1877a2e9abef4a5b89
2022-07-25T19:22:34.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-0_female-10_s961
1
null
transformers
33,437
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-0_female-10_s961 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 (es)](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_w2v2r_es_xls-r_gender_male-10_female-0_s109
7b0020455ef7c99303c0b8b5b90ca99b8a38466c
2022-07-25T19:27:28.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-10_female-0_s109
1
null
transformers
33,438
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-10_female-0_s109 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 (es)](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_w2v2r_es_xls-r_gender_male-10_female-0_s530
0f52580e185482cdc966ca702f2e9e9a0c0224b8
2022-07-25T19:32:22.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-10_female-0_s530
1
null
transformers
33,439
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-10_female-0_s530 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 (es)](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_w2v2r_es_xls-r_gender_male-10_female-0_s840
ee7e28ef949dea09bf8eb403b3624313a9481437
2022-07-25T19:36:56.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-10_female-0_s840
1
null
transformers
33,440
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-10_female-0_s840 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 (es)](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_w2v2r_es_xls-r_gender_male-2_female-8_s182
9b5cc8563659a4a6e5126bae658bec405aaa3727
2022-07-25T19:41:41.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-2_female-8_s182
1
null
transformers
33,441
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-2_female-8_s182 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 (es)](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_w2v2r_es_xls-r_gender_male-2_female-8_s772
e6b1a06567081c21a379637220e0abcf4cc7f6ac
2022-07-25T19:46:15.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-2_female-8_s772
1
null
transformers
33,442
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-2_female-8_s772 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 (es)](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_w2v2r_es_xls-r_gender_male-2_female-8_s786
e1fc2149bcd0e08ec6ba947cccbc7360c43084a5
2022-07-25T19:51:49.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-2_female-8_s786
1
null
transformers
33,443
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-2_female-8_s786 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 (es)](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_w2v2r_es_xls-r_gender_male-8_female-2_s235
79bc6171609d496ffe0c60dc61cfec8b0486d0c3
2022-07-25T19:56:44.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-8_female-2_s235
1
null
transformers
33,444
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-8_female-2_s235 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 (es)](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_w2v2r_es_xls-r_gender_male-8_female-2_s287
42615aba37ba6ed9caed4654dcda738f43f1a9b2
2022-07-25T20:01:41.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-8_female-2_s287
1
null
transformers
33,445
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-8_female-2_s287 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 (es)](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_w2v2r_es_xls-r_gender_male-8_female-2_s471
3eda8f7e8661cf6acd92ac346dcf62aa8111cd70
2022-07-25T20:13:40.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "es", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_es_xls-r_gender_male-8_female-2_s471
1
null
transformers
33,446
--- language: - es license: apache-2.0 tags: - automatic-speech-recognition - es datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_es_xls-r_gender_male-8_female-2_s471 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 (es)](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_w2v2r_fr_xls-r_accent_france-5_belgium-5_s42
c39704d7a7db04683f545cbf117feb7649f97191
2022-07-25T20:19:00.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-5_belgium-5_s42
1
null
transformers
33,447
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-5_belgium-5_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 (fr)](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_w2v2r_fr_xls-r_accent_france-5_belgium-5_s452
6e56f02408aab18446447548a97e4435bfb93353
2022-07-25T20:25:57.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-5_belgium-5_s452
1
null
transformers
33,448
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-5_belgium-5_s452 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 (fr)](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.
ultra-coder54732/xlnet-prop-16-train-set
bc8fc317b4c13201b87889119ccdf07b0cf35e0f
2022-07-25T22:48:19.000Z
[ "pytorch", "tensorboard", "xlnet", "text-classification", "transformers", "generated_from_trainer", "license:mit", "model-index" ]
text-classification
false
ultra-coder54732
null
ultra-coder54732/xlnet-prop-16-train-set
1
null
transformers
33,449
--- license: mit tags: - generated_from_trainer model-index: - name: xlnet-prop-16-train-set 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. --> # xlnet-prop-16-train-set This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown 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: 5e-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: 3.0 ### Training results ### Framework versions - Transformers 4.20.1 - Pytorch 1.12.0+cpu - Datasets 2.3.2 - Tokenizers 0.12.1
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-5_belgium-5_s941
e04eceab7d83efba60c186a946cb20432441cf21
2022-07-25T20:30:30.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-5_belgium-5_s941
1
null
transformers
33,450
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-5_belgium-5_s941 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 (fr)](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_w2v2r_fr_xls-r_accent_france-0_belgium-10_s198
2378b0f443c7206a23eab8f7db4b2125d2026a2b
2022-07-25T20:35:37.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-0_belgium-10_s198
1
null
transformers
33,451
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-0_belgium-10_s198 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 (fr)](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_w2v2r_fr_xls-r_accent_france-0_belgium-10_s376
1e1398c2faef881a2c15c4ba2d817a7423728fbb
2022-07-25T20:40:31.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-0_belgium-10_s376
1
null
transformers
33,452
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-0_belgium-10_s376 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 (fr)](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_w2v2r_fr_xls-r_accent_france-0_belgium-10_s513
ea38ae070f7947f826fed13d454263cb8ec32d82
2022-07-25T20:45:23.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-0_belgium-10_s513
1
null
transformers
33,453
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-0_belgium-10_s513 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 (fr)](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_w2v2r_fr_xls-r_accent_france-10_belgium-0_s350
f3b536b8f44b243c4ea69d067e3b796e36430a74
2022-07-25T20:50:21.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-10_belgium-0_s350
1
null
transformers
33,454
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-10_belgium-0_s350 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 (fr)](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_w2v2r_fr_xls-r_accent_france-10_belgium-0_s381
698ebb69bd2a2762e0c6422fddef38f114159db1
2022-07-25T20:55:08.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-10_belgium-0_s381
1
null
transformers
33,455
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-10_belgium-0_s381 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 (fr)](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_w2v2r_fr_xls-r_accent_france-10_belgium-0_s673
002c0f61c71f027430c90cb58510766c7d7e0e25
2022-07-25T21:00:07.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-10_belgium-0_s673
1
null
transformers
33,456
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-10_belgium-0_s673 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 (fr)](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_w2v2r_fr_xls-r_accent_france-2_belgium-8_s55
d0d1aacaf083a3b81e96da72aff1501fa4884c10
2022-07-25T21:04:38.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-2_belgium-8_s55
1
null
transformers
33,457
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-2_belgium-8_s55 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 (fr)](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_w2v2r_fr_xls-r_accent_france-2_belgium-8_s587
5c4dc8b7a6fd927949cf3fec626ecc6ba4a1f9ce
2022-07-25T21:09:22.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-2_belgium-8_s587
1
null
transformers
33,458
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-2_belgium-8_s587 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 (fr)](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_w2v2r_fr_xls-r_accent_france-2_belgium-8_s729
4b21d3fd6bef3bbdcbd16c6a3cf992520992a497
2022-07-25T21:14:21.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-2_belgium-8_s729
1
null
transformers
33,459
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-2_belgium-8_s729 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 (fr)](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_w2v2r_fr_xls-r_accent_france-8_belgium-2_s368
b2d3d4bd84712870243e3e9d0c7fc3133f928414
2022-07-25T21:19:12.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-8_belgium-2_s368
1
null
transformers
33,460
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-8_belgium-2_s368 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 (fr)](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_w2v2r_fr_xls-r_accent_france-8_belgium-2_s458
9a7868b2031b3d5a2ae15e5718221f4dd23441c9
2022-07-25T21:23:50.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-8_belgium-2_s458
1
null
transformers
33,461
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-8_belgium-2_s458 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 (fr)](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_w2v2r_fr_xls-r_accent_france-8_belgium-2_s543
614fc35cdb3f81eda935aa128cf1017697de7ca2
2022-07-25T21:28:45.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_accent_france-8_belgium-2_s543
1
null
transformers
33,462
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_accent_france-8_belgium-2_s543 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 (fr)](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_w2v2r_fr_xls-r_gender_male-5_female-5_s286
3161a24319caa24b02e37f2cfc9f8868e760d1d2
2022-07-25T21:33:38.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-5_female-5_s286
1
null
transformers
33,463
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-5_female-5_s286 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 (fr)](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_w2v2r_fr_xls-r_gender_male-5_female-5_s779
b2846d0b4fecf0b61e29ed28ae42b1bee2033a4c
2022-07-25T21:38:29.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-5_female-5_s779
1
null
transformers
33,464
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-5_female-5_s779 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 (fr)](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_w2v2r_fr_xls-r_gender_male-5_female-5_s916
4bb68c6bf15df9c915d4ab6a783e0a4ecef322c1
2022-07-25T21:42:58.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-5_female-5_s916
1
null
transformers
33,465
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-5_female-5_s916 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 (fr)](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_w2v2r_fr_xls-r_gender_male-0_female-10_s412
0dbbb47feb87457190c8271ee1b73e9a0df8d543
2022-07-25T21:47:50.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-0_female-10_s412
1
null
transformers
33,466
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-0_female-10_s412 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 (fr)](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_w2v2r_fr_xls-r_gender_male-0_female-10_s534
5511eeb288565736a9d52cfd02acb837675c1c81
2022-07-25T21:52:41.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-0_female-10_s534
1
null
transformers
33,467
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-0_female-10_s534 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 (fr)](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_w2v2r_fr_xls-r_gender_male-0_female-10_s895
94896de9273c5fbb2b1558bd574fdebade3c7d5e
2022-07-25T21:57:37.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-0_female-10_s895
1
null
transformers
33,468
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-0_female-10_s895 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 (fr)](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_w2v2r_fr_xls-r_gender_male-10_female-0_s559
22285ef79188e30f63c05faf4e3ecad5ee7f3e93
2022-07-25T22:02:28.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-10_female-0_s559
1
null
transformers
33,469
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-10_female-0_s559 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 (fr)](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_w2v2r_fr_xls-r_gender_male-10_female-0_s577
bd7f5b1ab9ae218d29f3cb13c34994faf1069f72
2022-07-25T22:07:24.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-10_female-0_s577
1
null
transformers
33,470
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-10_female-0_s577 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 (fr)](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_w2v2r_fr_xls-r_gender_male-10_female-0_s825
23d3ae5175efc492158d1ade831256eb742975d7
2022-07-25T22:12:15.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-10_female-0_s825
1
null
transformers
33,471
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-10_female-0_s825 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 (fr)](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_w2v2r_fr_xls-r_gender_male-2_female-8_s295
9547e0c9b0528a1bf71b3770dbcb0445c527524c
2022-07-25T22:17:07.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-2_female-8_s295
1
null
transformers
33,472
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-2_female-8_s295 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 (fr)](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_w2v2r_fr_xls-r_gender_male-2_female-8_s728
32f77e573660afd049724a6a6f5a6b93b698b672
2022-07-25T22:21:52.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-2_female-8_s728
1
null
transformers
33,473
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-2_female-8_s728 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 (fr)](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_w2v2r_fr_xls-r_gender_male-2_female-8_s886
cda6ab322349b88e642d44d95c22a9c43f5a5951
2022-07-25T22:26:53.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-2_female-8_s886
1
null
transformers
33,474
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-2_female-8_s886 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 (fr)](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_w2v2r_fr_xls-r_gender_male-8_female-2_s277
ce27ed71caea8e18e8cc203f2ff905370a0a92eb
2022-07-25T22:31:25.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-8_female-2_s277
1
null
transformers
33,475
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-8_female-2_s277 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 (fr)](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_w2v2r_fr_xls-r_gender_male-8_female-2_s659
9c5a40a07798896d4ef436a94159b614f9792287
2022-07-25T22:36:07.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2r_fr_xls-r_gender_male-8_female-2_s659
1
null
transformers
33,476
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2r_fr_xls-r_gender_male-8_female-2_s659 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 (fr)](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.
nakamura196/trocr-small-ndl
8dd0d2c4616e1212cedff5c147bfee6529b04914
2022-07-25T23:28:24.000Z
[ "pytorch", "vision-encoder-decoder", "transformers" ]
null
false
nakamura196
null
nakamura196/trocr-small-ndl
1
null
transformers
33,477
Entry not found
fujiki/t5-efficient-xl-ja_train4
eac4f1d78afe5ed1e7e297ef3cac964bdf96368b
2022-07-26T15:01:06.000Z
[ "pytorch", "tensorboard", "t5", "text2text-generation", "transformers", "autotrain_compatible" ]
text2text-generation
false
fujiki
null
fujiki/t5-efficient-xl-ja_train4
1
null
transformers
33,478
Entry not found
NimaBoscarino/July25Test
a26824db8aa951e7535116b5ed54e21e9d4ad9e7
2022-07-26T03:00:21.000Z
[ "pytorch", "distilbert", "feature-extraction", "sentence-transformers", "sentence-similarity", "transformers" ]
sentence-similarity
false
NimaBoscarino
null
NimaBoscarino/July25Test
1
null
sentence-transformers
33,479
--- pipeline_tag: sentence-similarity tags: - sentence-transformers - feature-extraction - sentence-similarity - transformers --- # NimaBoscarino/July25Test This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. <!--- Describe your model here --> ## Usage (Sentence-Transformers) Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: ``` pip install -U sentence-transformers ``` Then you can use the model like this: ```python from sentence_transformers import SentenceTransformer sentences = ["This is an example sentence", "Each sentence is converted"] model = SentenceTransformer('NimaBoscarino/July25Test') embeddings = model.encode(sentences) print(embeddings) ``` ## Usage (HuggingFace Transformers) Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings. ```python from transformers import AutoTokenizer, AutoModel import torch #Mean Pooling - Take attention mask into account for correct averaging def mean_pooling(model_output, attention_mask): token_embeddings = model_output[0] #First element of model_output contains all token embeddings input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float() return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9) # Sentences we want sentence embeddings for sentences = ['This is an example sentence', 'Each sentence is converted'] # Load model from HuggingFace Hub tokenizer = AutoTokenizer.from_pretrained('NimaBoscarino/July25Test') model = AutoModel.from_pretrained('NimaBoscarino/July25Test') # Tokenize sentences encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt') # Compute token embeddings with torch.no_grad(): model_output = model(**encoded_input) # Perform pooling. In this case, mean pooling. sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask']) print("Sentence embeddings:") print(sentence_embeddings) ``` ## Evaluation Results <!--- Describe how your model was evaluated --> For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=NimaBoscarino/July25Test) ## Training The model was trained with the parameters: **DataLoader**: `torch.utils.data.dataloader.DataLoader` of length 1 with parameters: ``` {'batch_size': 16, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'} ``` **Loss**: `sentence_transformers.losses.CosineSimilarityLoss.CosineSimilarityLoss` Parameters of the fit()-Method: ``` { "epochs": 2, "evaluation_steps": 0, "evaluator": "NoneType", "max_grad_norm": 1, "optimizer_class": "<class 'torch.optim.adamw.AdamW'>", "optimizer_params": { "lr": 2e-05 }, "scheduler": "WarmupLinear", "steps_per_epoch": null, "warmup_steps": 100, "weight_decay": 0.01 } ``` ## Full Model Architecture ``` SentenceTransformer( (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: DistilBertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False}) ) ``` ## Citing & Authors <!--- Describe where people can find more information -->
ultra-coder54732/distilbert-prop-16-train-set
cfa8ea3e27e6644bbf9d0d731b4e429fed6ee79a
2022-07-27T00:33:07.000Z
[ "pytorch", "tensorboard", "distilbert", "text-classification", "transformers", "generated_from_trainer", "license:apache-2.0", "model-index" ]
text-classification
false
ultra-coder54732
null
ultra-coder54732/distilbert-prop-16-train-set
1
null
transformers
33,480
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: distilbert-prop-16-train-set 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-prop-16-train-set This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on an unknown 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: 5e-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: 3.0 ### Training results ### Framework versions - Transformers 4.20.1 - Pytorch 1.12.0+cu113 - Datasets 2.4.0 - Tokenizers 0.12.1
rajat99/Fine_Tuning_XLSR_300M_testing_6_model
6a09b609df44569f006752f4a8c12a6d9f8cfa9c
2022-07-26T07:16:25.000Z
[ "pytorch", "tensorboard", "wav2vec2", "automatic-speech-recognition", "transformers", "generated_from_trainer", "license:apache-2.0", "model-index" ]
automatic-speech-recognition
false
rajat99
null
rajat99/Fine_Tuning_XLSR_300M_testing_6_model
1
null
transformers
33,481
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: Fine_Tuning_XLSR_300M_testing_6_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. --> # Fine_Tuning_XLSR_300M_testing_6_model This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.2263 - Wer: 1.0 ## 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: 0.0003 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 30 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:---:| | 5.466 | 23.53 | 400 | 3.2263 | 1.0 | ### Framework versions - Transformers 4.11.3 - Pytorch 1.10.0+cu113 - Datasets 1.18.3 - Tokenizers 0.10.3
obokkkk/bert-base-multilingual-cased-finetuned
70b09fad47b31fc30513699649b038cf9ac06eab
2022-07-26T08:07:23.000Z
[ "pytorch", "tensorboard", "bert", "question-answering", "transformers", "generated_from_trainer", "license:apache-2.0", "model-index", "autotrain_compatible" ]
question-answering
false
obokkkk
null
obokkkk/bert-base-multilingual-cased-finetuned
1
null
transformers
33,482
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: bert-base-multilingual-cased-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. --> # bert-base-multilingual-cased-finetuned This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 36 - total_train_batch_size: 288 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Framework versions - Transformers 4.20.1 - Pytorch 1.12.0+cu113 - Tokenizers 0.12.1
Frikallo/elonmusk
06f5f90f8c42e011fcaf0e700ab92a386618154a
2022-07-26T07:37:18.000Z
[ "pytorch", "tensorboard", "gpt2", "text-generation", "transformers", "generated_from_trainer", "license:mit", "model-index" ]
text-generation
false
Frikallo
null
Frikallo/elonmusk
1
null
transformers
33,483
--- license: mit tags: - generated_from_trainer model-index: - name: elonmusk 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. --> # elonmusk This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown 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: 0.0001372 - train_batch_size: 1 - eval_batch_size: 8 - seed: 2483812281 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1.0 ### Training results ### Framework versions - Transformers 4.20.1 - Pytorch 1.9.1+cu111 - Datasets 2.3.2 - Tokenizers 0.12.1
Kushala/wav2vec2-base-timit-demo-google-colab
3a4e2da388d5ba74a172bee6676a5c642136a717
2022-07-26T10:07:09.000Z
[ "pytorch", "tensorboard", "wav2vec2", "automatic-speech-recognition", "transformers", "generated_from_trainer", "license:apache-2.0", "model-index" ]
automatic-speech-recognition
false
Kushala
null
Kushala/wav2vec2-base-timit-demo-google-colab
1
null
transformers
33,484
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: wav2vec2-base-timit-demo-google-colab 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. --> # wav2vec2-base-timit-demo-google-colab This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5195 - Wer: 0.3386 ## 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: 0.0001 - 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 - lr_scheduler_warmup_steps: 1000 - num_epochs: 30 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:------:| | 3.5345 | 1.0 | 500 | 2.1466 | 1.0010 | | 0.949 | 2.01 | 1000 | 0.5687 | 0.5492 | | 0.445 | 3.01 | 1500 | 0.4562 | 0.4717 | | 0.2998 | 4.02 | 2000 | 0.4154 | 0.4401 | | 0.2242 | 5.02 | 2500 | 0.3887 | 0.4034 | | 0.1834 | 6.02 | 3000 | 0.4262 | 0.3905 | | 0.1573 | 7.03 | 3500 | 0.4200 | 0.3927 | | 0.1431 | 8.03 | 4000 | 0.4194 | 0.3869 | | 0.1205 | 9.04 | 4500 | 0.4600 | 0.3912 | | 0.1082 | 10.04 | 5000 | 0.4613 | 0.3776 | | 0.0984 | 11.04 | 5500 | 0.4926 | 0.3860 | | 0.0872 | 12.05 | 6000 | 0.4869 | 0.3780 | | 0.0826 | 13.05 | 6500 | 0.5033 | 0.3690 | | 0.0717 | 14.06 | 7000 | 0.4827 | 0.3791 | | 0.0658 | 15.06 | 7500 | 0.4816 | 0.3650 | | 0.0579 | 16.06 | 8000 | 0.5433 | 0.3689 | | 0.056 | 17.07 | 8500 | 0.5513 | 0.3672 | | 0.0579 | 18.07 | 9000 | 0.4813 | 0.3632 | | 0.0461 | 19.08 | 9500 | 0.4846 | 0.3501 | | 0.0431 | 20.08 | 10000 | 0.5449 | 0.3637 | | 0.043 | 21.08 | 10500 | 0.4906 | 0.3538 | | 0.0334 | 22.09 | 11000 | 0.5081 | 0.3477 | | 0.0322 | 23.09 | 11500 | 0.5184 | 0.3439 | | 0.0316 | 24.1 | 12000 | 0.5412 | 0.3450 | | 0.0262 | 25.1 | 12500 | 0.5113 | 0.3425 | | 0.0267 | 26.1 | 13000 | 0.4888 | 0.3414 | | 0.0258 | 27.11 | 13500 | 0.5071 | 0.3371 | | 0.0226 | 28.11 | 14000 | 0.5311 | 0.3380 | | 0.0233 | 29.12 | 14500 | 0.5195 | 0.3386 | ### Framework versions - Transformers 4.17.0 - Pytorch 1.12.0+cu113 - Datasets 1.18.3 - Tokenizers 0.12.1
FAICAM/wav2vec2-base-timit-demo-google-colab
c6737330587df605e8164c635f2bc1e6d6aa040f
2022-07-26T11:07:42.000Z
[ "pytorch", "tensorboard", "wav2vec2", "automatic-speech-recognition", "transformers", "generated_from_trainer", "license:apache-2.0", "model-index" ]
automatic-speech-recognition
false
FAICAM
null
FAICAM/wav2vec2-base-timit-demo-google-colab
1
null
transformers
33,485
--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: wav2vec2-base-timit-demo-google-colab 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. --> # wav2vec2-base-timit-demo-google-colab This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5725 - Wer: 0.3413 ## 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: 0.0001 - 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 - lr_scheduler_warmup_steps: 1000 - num_epochs: 30 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:------:| | 3.508 | 1.0 | 500 | 1.9315 | 0.9962 | | 0.8832 | 2.01 | 1000 | 0.5552 | 0.5191 | | 0.4381 | 3.01 | 1500 | 0.4451 | 0.4574 | | 0.2983 | 4.02 | 2000 | 0.4096 | 0.4265 | | 0.2232 | 5.02 | 2500 | 0.4280 | 0.4083 | | 0.1811 | 6.02 | 3000 | 0.4307 | 0.3942 | | 0.1548 | 7.03 | 3500 | 0.4453 | 0.3889 | | 0.1367 | 8.03 | 4000 | 0.5043 | 0.4138 | | 0.1238 | 9.04 | 4500 | 0.4530 | 0.3807 | | 0.1072 | 10.04 | 5000 | 0.4435 | 0.3660 | | 0.0978 | 11.04 | 5500 | 0.4739 | 0.3676 | | 0.0887 | 12.05 | 6000 | 0.5052 | 0.3761 | | 0.0813 | 13.05 | 6500 | 0.5098 | 0.3619 | | 0.0741 | 14.06 | 7000 | 0.4666 | 0.3602 | | 0.0654 | 15.06 | 7500 | 0.5642 | 0.3657 | | 0.0589 | 16.06 | 8000 | 0.5489 | 0.3638 | | 0.0559 | 17.07 | 8500 | 0.5260 | 0.3598 | | 0.0562 | 18.07 | 9000 | 0.5250 | 0.3640 | | 0.0448 | 19.08 | 9500 | 0.5215 | 0.3569 | | 0.0436 | 20.08 | 10000 | 0.5117 | 0.3560 | | 0.0412 | 21.08 | 10500 | 0.4910 | 0.3570 | | 0.0336 | 22.09 | 11000 | 0.5221 | 0.3524 | | 0.031 | 23.09 | 11500 | 0.5278 | 0.3480 | | 0.0339 | 24.1 | 12000 | 0.5353 | 0.3486 | | 0.0278 | 25.1 | 12500 | 0.5342 | 0.3462 | | 0.0251 | 26.1 | 13000 | 0.5399 | 0.3439 | | 0.0242 | 27.11 | 13500 | 0.5626 | 0.3431 | | 0.0214 | 28.11 | 14000 | 0.5749 | 0.3408 | | 0.0216 | 29.12 | 14500 | 0.5725 | 0.3413 | ### Framework versions - Transformers 4.17.0 - Pytorch 1.12.0+cu113 - Datasets 1.18.3 - Tokenizers 0.12.1
nielsr/donut-proto
8b4bfcdc09728efa70723978563979ba9a708e5a
2022-07-26T09:33:41.000Z
[ "pytorch", "vision-encoder-decoder", "transformers" ]
null
false
nielsr
null
nielsr/donut-proto
1
null
transformers
33,486
Entry not found
WENGSYX/Dagnosis_Chinese_CPT
112f102f845c2dfccf16808f018796db636243e7
2022-07-26T09:54:15.000Z
[ "pytorch", "bart", "feature-extraction", "transformers", "license:mit" ]
feature-extraction
false
WENGSYX
null
WENGSYX/Dagnosis_Chinese_CPT
1
null
transformers
33,487
--- license: mit ---
WENGSYX/Medical_Report_Chinese_CPT
78223d8f1ab3876b9b8720d97f03809385bb5b60
2022-07-26T16:42:44.000Z
[ "pytorch", "bart", "feature-extraction", "transformers", "license:mit" ]
feature-extraction
false
WENGSYX
null
WENGSYX/Medical_Report_Chinese_CPT
1
null
transformers
33,488
--- license: mit ---
NbAiLab/wav2vec2-1b-npsc-nst-bokmaal-repaired
10d29b8aaf02cb064e23d30c001e8ba8cc59ad75
2022-07-30T09:26:20.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "transformers" ]
automatic-speech-recognition
false
NbAiLab
null
NbAiLab/wav2vec2-1b-npsc-nst-bokmaal-repaired
1
null
transformers
33,489
Entry not found
SummerChiam/rust_image_classification_8
9379fd7ed72261c23619d651fd79079a12994fa8
2022-07-26T13:28:11.000Z
[ "pytorch", "tensorboard", "vit", "image-classification", "transformers", "huggingpics", "model-index" ]
image-classification
false
SummerChiam
null
SummerChiam/rust_image_classification_8
1
null
transformers
33,490
--- tags: - image-classification - pytorch - huggingpics metrics: - accuracy model-index: - name: rust_image_classification_3 results: - task: name: Image Classification type: image-classification metrics: - name: Accuracy type: accuracy value: 0.9594936966896057 --- # rust_image_classification_3 Autogenerated by HuggingPics🤗🖼️ Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb). Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics). ## Example Images #### nonrust ![nonrust](images/nonrust.png) #### rust ![rust](images/rust.png)
domenicrosati/deberta-v3-large-finetuned-synthetic-translated-only
55b85ce075cb135c74621bccab5ba930dee6b9cb
2022-07-26T22:34:44.000Z
[ "pytorch", "tensorboard", "deberta-v2", "text-classification", "transformers", "generated_from_trainer", "license:mit", "model-index" ]
text-classification
false
domenicrosati
null
domenicrosati/deberta-v3-large-finetuned-synthetic-translated-only
1
null
transformers
33,491
--- license: mit tags: - text-classification - generated_from_trainer metrics: - f1 - precision - recall model-index: - name: deberta-v3-large-finetuned-synthetic-translated-only 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. --> # deberta-v3-large-finetuned-synthetic-translated-only This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0005 - F1: 0.9961 - Precision: 1.0 - Recall: 0.9922 ## 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: 6e-06 - 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 - lr_scheduler_warmup_steps: 50 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | |:-------------:|:-----:|:-----:|:---------------:|:------:|:---------:|:------:| | 0.0065 | 1.0 | 10158 | 0.0022 | 0.9887 | 0.9962 | 0.9813 | | 0.0006 | 2.0 | 20316 | 0.0030 | 0.9887 | 0.9962 | 0.9813 | | 0.0008 | 3.0 | 30474 | 0.0029 | 0.9906 | 0.9962 | 0.9851 | ### Framework versions - Transformers 4.18.0 - Pytorch 1.11.0 - Datasets 2.1.0 - Tokenizers 0.12.1
huggingtweets/tojibaceo-tojibawhiteroom
68cce5380f7c55da652bcdfb65b957961e3d6261
2022-07-26T15:55:19.000Z
[ "pytorch", "gpt2", "text-generation", "en", "transformers", "huggingtweets" ]
text-generation
false
huggingtweets
null
huggingtweets/tojibaceo-tojibawhiteroom
1
null
transformers
33,492
--- language: en thumbnail: http://www.huggingtweets.com/tojibaceo-tojibawhiteroom/1658850915163/predictions.png tags: - huggingtweets widget: - text: "My dream is" --- <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1508824472924659725/267f4Lkm_400x400.jpg&#39;)"> </div> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1509337156787003394/WjOdf_-m_400x400.jpg&#39;)"> </div> <div style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)"> </div> </div> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI CYBORG 🤖</div> <div style="text-align: center; font-size: 16px; font-weight: 800">Tojiba CPU Corp (🏭,🏭) & Tojiba White Room (T__T).1</div> <div style="text-align: center; font-size: 14px;">@tojibaceo-tojibawhiteroom</div> </div> I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets). Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)! ## How does it work? The model uses the following pipeline. ![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true) To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI). ## Training data The model was trained on tweets from Tojiba CPU Corp (🏭,🏭) & Tojiba White Room (T__T).1. | Data | Tojiba CPU Corp (🏭,🏭) | Tojiba White Room (T__T).1 | | --- | --- | --- | | Tweets downloaded | 1489 | 624 | | Retweets | 723 | 0 | | Short tweets | 259 | 80 | | Tweets kept | 507 | 544 | [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2jak2xfb/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline. ## Training procedure The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @tojibaceo-tojibawhiteroom's tweets. Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/t112mifn) for full transparency and reproducibility. At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/t112mifn/artifacts) is logged and versioned. ## How to use You can use this model directly with a pipeline for text generation: ```python from transformers import pipeline generator = pipeline('text-generation', model='huggingtweets/tojibaceo-tojibawhiteroom') generator("My dream is", num_return_sequences=5) ``` ## Limitations and bias The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias). In addition, the data present in the user's tweets further affects the text generated by the model. ## About *Built by Boris Dayma* [![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)
schnell/bert-small-juman-bpe
5ab23c6caed1309f224140984fc3422981c4ed4a
2022-07-29T15:15:11.000Z
[ "pytorch", "tensorboard", "bert", "fill-mask", "transformers", "generated_from_trainer", "model-index", "autotrain_compatible" ]
fill-mask
false
schnell
null
schnell/bert-small-juman-bpe
1
null
transformers
33,493
--- tags: - generated_from_trainer metrics: - accuracy model-index: - name: bert-small-juman-bpe 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-small-juman-bpe This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. It achieves the following results on the evaluation set: - Accuracy: 0.6317 - Loss: 1.7829 ## 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: 0.0001 - train_batch_size: 256 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 3 - total_train_batch_size: 768 - total_eval_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.01 - num_epochs: 14 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Accuracy | Validation Loss | |:-------------:|:-----:|:------:|:--------:|:---------------:| | 2.3892 | 1.0 | 69472 | 0.5637 | 2.2498 | | 2.2219 | 2.0 | 138944 | 0.5873 | 2.0785 | | 2.1453 | 3.0 | 208416 | 0.5984 | 2.0019 | | 2.1 | 4.0 | 277888 | 0.6059 | 1.9531 | | 2.068 | 5.0 | 347360 | 0.6106 | 1.9169 | | 2.0405 | 6.0 | 416832 | 0.6146 | 1.8921 | | 2.0174 | 7.0 | 486304 | 0.6175 | 1.8711 | | 2.0002 | 8.0 | 555776 | 0.6205 | 1.8527 | | 1.9838 | 9.0 | 625248 | 0.6225 | 1.8381 | | 1.9691 | 10.0 | 694720 | 0.6248 | 1.8239 | | 1.9551 | 11.0 | 764192 | 0.6265 | 1.8125 | | 1.9406 | 12.0 | 833664 | 0.6288 | 1.8002 | | 1.9293 | 13.0 | 903136 | 0.6310 | 1.7871 | | 1.9247 | 14.0 | 972608 | 0.6317 | 1.7829 | ### Framework versions - Transformers 4.19.2 - Pytorch 1.12.0+cu116 - Datasets 2.2.2 - Tokenizers 0.12.1
huggingtweets/jockforbrains
c1ab58a8bdda06783f8a8e35dbe71b0f5eaf218d
2022-07-26T16:25:23.000Z
[ "pytorch", "gpt2", "text-generation", "en", "transformers", "huggingtweets" ]
text-generation
false
huggingtweets
null
huggingtweets/jockforbrains
1
null
transformers
33,494
--- language: en thumbnail: http://www.huggingtweets.com/jockforbrains/1658852709222/predictions.png tags: - huggingtweets widget: - text: "My dream is" --- <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1492447040193900546/LtTdjrY7_400x400.jpg&#39;)"> </div> <div style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)"> </div> <div style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)"> </div> </div> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div> <div style="text-align: center; font-size: 16px; font-weight: 800">JockForBrains (☣️ May contain morphs)</div> <div style="text-align: center; font-size: 14px;">@jockforbrains</div> </div> I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets). Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)! ## How does it work? The model uses the following pipeline. ![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true) To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI). ## Training data The model was trained on tweets from JockForBrains (☣️ May contain morphs). | Data | JockForBrains (☣️ May contain morphs) | | --- | --- | | Tweets downloaded | 3238 | | Retweets | 211 | | Short tweets | 467 | | Tweets kept | 2560 | [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2jsjyesm/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline. ## Training procedure The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @jockforbrains's tweets. Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/zi3c9sw9) for full transparency and reproducibility. At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/zi3c9sw9/artifacts) is logged and versioned. ## How to use You can use this model directly with a pipeline for text generation: ```python from transformers import pipeline generator = pipeline('text-generation', model='huggingtweets/jockforbrains') generator("My dream is", num_return_sequences=5) ``` ## Limitations and bias The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias). In addition, the data present in the user's tweets further affects the text generated by the model. ## About *Built by Boris Dayma* [![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)
carblacac/distilbert-base-uncased-finetuned-emotion
33838e5f0a062c700303e104afcb24b0975e568e
2022-07-27T18:28:54.000Z
[ "pytorch", "tensorboard", "distilbert", "text-classification", "dataset:emotion", "transformers", "generated_from_trainer", "license:apache-2.0", "model-index" ]
text-classification
false
carblacac
null
carblacac/distilbert-base-uncased-finetuned-emotion
1
null
transformers
33,495
--- license: apache-2.0 tags: - generated_from_trainer datasets: - emotion metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-emotion results: - task: name: Text Classification type: text-classification dataset: name: emotion type: emotion args: default metrics: - name: Accuracy type: accuracy value: 0.9215 - name: F1 type: f1 value: 0.9214820157277583 --- <!-- 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-emotion This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset. It achieves the following results on the evaluation set: - Loss: 0.2197 - Accuracy: 0.9215 - F1: 0.9215 ## 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: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.8026 | 1.0 | 250 | 0.3133 | 0.905 | 0.9022 | | 0.2468 | 2.0 | 500 | 0.2197 | 0.9215 | 0.9215 | ### Framework versions - Transformers 4.18.0 - Pytorch 1.11.0+cu102 - Datasets 2.1.0 - Tokenizers 0.12.1
huggingtweets/bearfoothunter1-jockforbrains-recentrift
e24a77838a031bd29259dd1f4f9779fe42e1e086
2022-07-26T16:57:52.000Z
[ "pytorch", "gpt2", "text-generation", "en", "transformers", "huggingtweets" ]
text-generation
false
huggingtweets
null
huggingtweets/bearfoothunter1-jockforbrains-recentrift
1
null
transformers
33,496
--- language: en thumbnail: http://www.huggingtweets.com/bearfoothunter1-jockforbrains-recentrift/1658853737112/predictions.png tags: - huggingtweets widget: - text: "My dream is" --- <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1492447040193900546/LtTdjrY7_400x400.jpg&#39;)"> </div> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1550974872502796289/7i5bgWY2_400x400.jpg&#39;)"> </div> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1015932356937560069/EJSUv5Uk_400x400.jpg&#39;)"> </div> </div> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI CYBORG 🤖</div> <div style="text-align: center; font-size: 16px; font-weight: 800">JockForBrains (☣️ May contain morphs) & Demonic Executioner & the real bearfoothunter 🇺🇦🇺🇦🇺🇦</div> <div style="text-align: center; font-size: 14px;">@bearfoothunter1-jockforbrains-recentrift</div> </div> I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets). Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)! ## How does it work? The model uses the following pipeline. ![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true) To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI). ## Training data The model was trained on tweets from JockForBrains (☣️ May contain morphs) & Demonic Executioner & the real bearfoothunter 🇺🇦🇺🇦🇺🇦. | Data | JockForBrains (☣️ May contain morphs) | Demonic Executioner | the real bearfoothunter 🇺🇦🇺🇦🇺🇦 | | --- | --- | --- | --- | | Tweets downloaded | 3238 | 2261 | 3248 | | Retweets | 211 | 177 | 64 | | Short tweets | 467 | 104 | 746 | | Tweets kept | 2560 | 1980 | 2438 | [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2susnztb/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline. ## Training procedure The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @bearfoothunter1-jockforbrains-recentrift's tweets. Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/18fa8jhh) for full transparency and reproducibility. At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/18fa8jhh/artifacts) is logged and versioned. ## How to use You can use this model directly with a pipeline for text generation: ```python from transformers import pipeline generator = pipeline('text-generation', model='huggingtweets/bearfoothunter1-jockforbrains-recentrift') generator("My dream is", num_return_sequences=5) ``` ## Limitations and bias The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias). In addition, the data present in the user's tweets further affects the text generated by the model. ## About *Built by Boris Dayma* [![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)
huggingtweets/surlaroute
ce5ea0fe4a6e21ba60d6a157bab803841d47714a
2022-07-26T16:42:31.000Z
[ "pytorch", "gpt2", "text-generation", "en", "transformers", "huggingtweets" ]
text-generation
false
huggingtweets
null
huggingtweets/surlaroute
1
null
transformers
33,497
--- language: en thumbnail: http://www.huggingtweets.com/surlaroute/1658853747255/predictions.png tags: - huggingtweets widget: - text: "My dream is" --- <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1305228695444090882/aU_Vlnvg_400x400.jpg&#39;)"> </div> <div style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)"> </div> <div style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)"> </div> </div> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div> <div style="text-align: center; font-size: 16px; font-weight: 800">Melody 🧜🏻‍♀️</div> <div style="text-align: center; font-size: 14px;">@surlaroute</div> </div> I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets). Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)! ## How does it work? The model uses the following pipeline. ![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true) To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI). ## Training data The model was trained on tweets from Melody 🧜🏻‍♀️. | Data | Melody 🧜🏻‍♀️ | | --- | --- | | Tweets downloaded | 3245 | | Retweets | 114 | | Short tweets | 351 | | Tweets kept | 2780 | [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/k1hti8dn/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline. ## Training procedure The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @surlaroute's tweets. Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/cffupuun) for full transparency and reproducibility. At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/cffupuun/artifacts) is logged and versioned. ## How to use You can use this model directly with a pipeline for text generation: ```python from transformers import pipeline generator = pipeline('text-generation', model='huggingtweets/surlaroute') generator("My dream is", num_return_sequences=5) ``` ## Limitations and bias The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias). In addition, the data present in the user's tweets further affects the text generated by the model. ## About *Built by Boris Dayma* [![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)
phjhk/hklegal-xlm-r-large-t
4e4df9796c30d2e572c1c2104030396d1b716c0f
2022-07-29T14:50:13.000Z
[ "pytorch", "xlm-roberta", "fill-mask", "multilingual", "af", "am", "ar", "as", "az", "be", "bg", "bn", "br", "bs", "ca", "cs", "cy", "da", "de", "el", "en", "eo", "es", "et", "eu", "fa", "fi", "fr", "fy", "ga", "gd", "gl", "gu", "ha", "he", "hi", "hr", "hu", "hy", "id", "is", "it", "ja", "jv", "ka", "kk", "km", "kn", "ko", "ku", "ky", "la", "lo", "lt", "lv", "mg", "mk", "ml", "mn", "mr", "ms", "my", "ne", "nl", "no", "om", "or", "pa", "pl", "ps", "pt", "ro", "ru", "sa", "sd", "si", "sk", "sl", "so", "sq", "sr", "su", "sv", "sw", "ta", "te", "th", "tl", "tr", "ug", "uk", "ur", "uz", "vi", "xh", "yi", "zh", "arxiv:1911.02116", "transformers", "autotrain_compatible" ]
fill-mask
false
phjhk
null
phjhk/hklegal-xlm-r-large-t
1
null
transformers
33,498
--- language: - multilingual - af - am - ar - as - az - be - bg - bn - br - bs - ca - cs - cy - da - de - el - en - eo - es - et - eu - fa - fi - fr - fy - ga - gd - gl - gu - ha - he - hi - hr - hu - hy - id - is - it - ja - jv - ka - kk - km - kn - ko - ku - ky - la - lo - lt - lv - mg - mk - ml - mn - mr - ms - my - ne - nl - no - om - or - pa - pl - ps - pt - ro - ru - sa - sd - si - sk - sl - so - sq - sr - su - sv - sw - ta - te - th - tl - tr - ug - uk - ur - uz - vi - xh - yi - zh --- # Model Description The XLM-RoBERTa model was proposed in [Unsupervised Cross-lingual Representation Learning at Scale](https://arxiv.org/abs/1911.02116) by Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer and Veselin Stoyanov. It is based on Facebook's RoBERTa model released in 2019. It is a large multi-lingual language model, trained on 2.5TB of filtered CommonCrawl data. This model is [XLM-RoBERTa-large](https://huggingface.co/xlm-roberta-large) fine-tuned with the [conll2003](https://huggingface.co/datasets/conll2003) dataset in English. - **Developed by:** See [associated paper](https://arxiv.org/abs/1911.02116) - **Model type:** Multi-lingual language model - **Language(s) (NLP) or Countries (images):** XLM-RoBERTa is a multilingual model trained on 100 different languages; see [GitHub Repo](https://github.com/facebookresearch/fairseq/tree/main/examples/xlmr) for full list; model is fine-tuned on a dataset in English - **Related Models:** [RoBERTa](https://huggingface.co/roberta-base), [XLM](https://huggingface.co/docs/transformers/model_doc/xlm) - **Parent Model:** [XLM-RoBERTa-large](https://huggingface.co/xlm-roberta-large) Hong Kong Legal Information Institute [HKILL](https://www.hklii.hk/eng/) is a free, independent, non-profit document database providing the public with legal information relating to Hong Kong. We finetune the XLM-RoBERTa on the HKILL datasets. It contains docments # Uses The model is a pretrained-finetuned language model. The model can be used for document classification, Named Entity Recognition (NER), especially on legal domain. ```python >>> from transformers import pipeline,AutoTokenizer,AutoModelForTokenClassification >>> tokenizer = AutoTokenizer.from_pretrained("hklegal-xlm-r-large-t") >>> model = AutoModelForTokenClassification.from_pretrained("hklegal-xlm-r-large-t") >>> classifier = pipeline("ner", model=model, tokenizer=tokenizer) >>> classifier("Alya told Jasmine that Andrew could pay with cash..") ``` # Citation **BibTeX:** ```bibtex @article{conneau2019unsupervised, title={Unsupervised Cross-lingual Representation Learning at Scale}, author={Conneau, Alexis and Khandelwal, Kartikay and Goyal, Naman and Chaudhary, Vishrav and Wenzek, Guillaume and Guzm{\'a}n, Francisco and Grave, Edouard and Ott, Myle and Zettlemoyer, Luke and Stoyanov, Veselin}, journal={arXiv preprint arXiv:1911.02116}, year={2019} } ```
huggingtweets/hiddenlure
718830623afe76235171480170cd4dc345a863e2
2022-07-26T17:17:28.000Z
[ "pytorch", "gpt2", "text-generation", "en", "transformers", "huggingtweets" ]
text-generation
false
huggingtweets
null
huggingtweets/hiddenlure
1
null
transformers
33,499
--- language: en thumbnail: http://www.huggingtweets.com/hiddenlure/1658855843772/predictions.png tags: - huggingtweets widget: - text: "My dream is" --- <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1541995552505831424/K1gtBapk_400x400.jpg&#39;)"> </div> <div style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)"> </div> <div style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)"> </div> </div> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div> <div style="text-align: center; font-size: 16px; font-weight: 800">Hidden</div> <div style="text-align: center; font-size: 14px;">@hiddenlure</div> </div> I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets). Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)! ## How does it work? The model uses the following pipeline. ![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true) To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI). ## Training data The model was trained on tweets from Hidden. | Data | Hidden | | --- | --- | | Tweets downloaded | 376 | | Retweets | 96 | | Short tweets | 24 | | Tweets kept | 256 | [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/174g7le6/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline. ## Training procedure The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @hiddenlure's tweets. Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3oy7jn9e) for full transparency and reproducibility. At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3oy7jn9e/artifacts) is logged and versioned. ## How to use You can use this model directly with a pipeline for text generation: ```python from transformers import pipeline generator = pipeline('text-generation', model='huggingtweets/hiddenlure') generator("My dream is", num_return_sequences=5) ``` ## Limitations and bias The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias). In addition, the data present in the user's tweets further affects the text generated by the model. ## About *Built by Boris Dayma* [![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)