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davanstrien
/
pytorchmodelmetadata

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jonatasgrosman/exp_w2v2t_it_vp-100k_s449
76cbb34cfc7aa892c277c37ccdbcee79ebce52b5
2022-07-08T19:01:30.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-100k_s449
2
null
transformers
26,700
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-100k_s449 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
huggingtweets/_anushkasharmaa
84afd581cc7f37d41d37565201c4229ccd75df93
2022-07-08T19:04:13.000Z
[ "pytorch", "gpt2", "text-generation", "en", "transformers", "huggingtweets" ]
text-generation
false
huggingtweets
null
huggingtweets/_anushkasharmaa
2
null
transformers
26,701
--- language: en thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true 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/1544699011642171392/mEzKAPWL_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">Anushka Sharma</div> <div style="text-align: center; font-size: 14px;">@_anushkasharmaa</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 Anushka Sharma. | Data | Anushka Sharma | | --- | --- | | Tweets downloaded | 431 | | Retweets | 129 | | Short tweets | 80 | | Tweets kept | 222 | [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1z7v8rf0/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 @_anushkasharmaa's tweets. Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1qxdz9eg) for full transparency and reproducibility. At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1qxdz9eg/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/_anushkasharmaa') 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)
jonatasgrosman/exp_w2v2t_it_vp-100k_s358
55e10b052935bab77f3e4d376b0273f7960c5b5c
2022-07-08T19:05:46.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-100k_s358
2
null
transformers
26,702
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-100k_s358 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_xlsr-53_s387
595d707de8e476caec5caa97a5c22903868a6f28
2022-07-08T19:09:45.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_xlsr-53_s387
2
null
transformers
26,703
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_xlsr-53_s387 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_xlsr-53_s237
ed0affa2a883d78401eaef1c4a61de3acfa5b7b3
2022-07-08T19:12:58.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_xlsr-53_s237
2
null
transformers
26,704
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_xlsr-53_s237 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_xlsr-53_s79
1de453033bdcab0db8c9a144d6a245e8c8e6361e
2022-07-08T19:16:35.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_xlsr-53_s79
2
null
transformers
26,705
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_xlsr-53_s79 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_unispeech_s714
bc88e58780d56bc4e31ffcb97bcedf35e5fcce50
2022-07-08T19:20:02.000Z
[ "pytorch", "unispeech", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_unispeech_s714
2
null
transformers
26,706
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_unispeech_s714 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_unispeech_s626
579ef119ba31b5a8a93767e13d974c2cc37c4fff
2022-07-08T19:23:51.000Z
[ "pytorch", "unispeech", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_unispeech_s626
2
null
transformers
26,707
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_unispeech_s626 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_unispeech_s156
c52675968f981a3fc866899f9d837768d848e5c5
2022-07-08T19:27:36.000Z
[ "pytorch", "unispeech", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_unispeech_s156
2
null
transformers
26,708
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_unispeech_s156 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_hubert_s722
d71779504448205087aa46f365411ea1ddcc4bd5
2022-07-08T19:30:54.000Z
[ "pytorch", "hubert", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_hubert_s722
2
null
transformers
26,709
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_hubert_s722 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_hubert_s21
b3c4c4cc3f62182cc91644edae5b5b94e621e86e
2022-07-08T19:37:22.000Z
[ "pytorch", "hubert", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_hubert_s21
2
null
transformers
26,710
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_hubert_s21 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_hubert_s474
a198274e60fddc1a228b27e51debb6369156de3e
2022-07-08T19:40:35.000Z
[ "pytorch", "hubert", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_hubert_s474
2
null
transformers
26,711
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_hubert_s474 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-sv_s791
e2a61ecadac3f7cb3238cb91d9569e10539502a9
2022-07-08T19:44:09.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-sv_s791
2
null
transformers
26,712
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-sv_s791 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-sv_s149
422551a341c41597998632d38c21801896a22759
2022-07-08T19:47:29.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-sv_s149
2
null
transformers
26,713
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-sv_s149 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-sv_s1
d6662142b3de03328160b43993b33487f8c6c068
2022-07-08T19:51:06.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-sv_s1
2
null
transformers
26,714
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-sv_s1 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_no-pretraining_s615
9ebb422a252e9aea7ed72b3469e76bf8d6e883fd
2022-07-08T19:55:28.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_no-pretraining_s615
2
null
transformers
26,715
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_no-pretraining_s615 Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_no-pretraining_s842
8701b90611612fbc83d824aa501bd6aa0d888088
2022-07-08T19:58:51.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_no-pretraining_s842
2
null
transformers
26,716
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_no-pretraining_s842 Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_no-pretraining_s764
262a8f1ec983235fe7906fb331188bc6efeebdbe
2022-07-08T20:02:47.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_no-pretraining_s764
2
null
transformers
26,717
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_no-pretraining_s764 Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_wavlm_s895
4a6d513ec92fec4d167d574ea8868d246682bed8
2022-07-08T20:09:44.000Z
[ "pytorch", "wavlm", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_wavlm_s895
2
null
transformers
26,718
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_wavlm_s895 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_wavlm_s25
41c9c6a3117ae856efae28b13ddf75d23ce50359
2022-07-08T20:13:30.000Z
[ "pytorch", "wavlm", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_wavlm_s25
2
null
transformers
26,719
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_wavlm_s25 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s213
e37623a41c475aa1d3bd0fe1fa520b3776f75567
2022-07-08T20:16:37.000Z
[ "pytorch", "unispeech", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s213
2
null
transformers
26,720
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_unispeech-ml_s213 Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s246
4a357fb104ea9254065c8b668421e830dd78cee0
2022-07-08T20:20:05.000Z
[ "pytorch", "unispeech", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s246
2
null
transformers
26,721
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_unispeech-ml_s246 Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784
0ecc87b8dd6db754b70712b7b43aab0030062568
2022-07-08T20:23:31.000Z
[ "pytorch", "unispeech", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784
2
null
transformers
26,722
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_unispeech-ml_s784 Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-fr_s821
370856b51df145c3fc8174c70766fb6ed5554d16
2022-07-08T20:27:50.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-fr_s821
2
null
transformers
26,723
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-fr_s821 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-fr_s579
bc8c6fda9172202f8d2cc79f1545f264adcc7acf
2022-07-08T20:32:13.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-fr_s579
2
null
transformers
26,724
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-fr_s579 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-fr_s557
29128deecea0e8547dbe1dd48fb032b97ad2e4ea
2022-07-08T20:35:34.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-fr_s557
2
null
transformers
26,725
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-fr_s557 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-es_s33
56ab3820dc5e4cb61653d8eebdd5975520b955d4
2022-07-08T20:39:11.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-es_s33
2
null
transformers
26,726
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-es_s33 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-es_s496
db98f18235704a6c3f6f861af36987d1f11cf196
2022-07-08T20:42:33.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-es_s496
2
null
transformers
26,727
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-es_s496 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-es_s878
2d4abb127a6b8a6519c6f9f0e220adb8a1a3f006
2022-07-08T20:47:26.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-es_s878
2
null
transformers
26,728
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-es_s878 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
huggingtweets/redo
68672fd8f6f9b1b9b860e94473d01c081d36bb95
2022-07-08T21:02:22.000Z
[ "pytorch", "gpt2", "text-generation", "en", "transformers", "huggingtweets" ]
text-generation
false
huggingtweets
null
huggingtweets/redo
2
null
transformers
26,729
--- language: en thumbnail: http://www.huggingtweets.com/redo/1657314137996/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/809537557943881728/GU7lSXyY_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">Gregory Renard</div> <div style="text-align: center; font-size: 14px;">@redo</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 Gregory Renard. | Data | Gregory Renard | | --- | --- | | Tweets downloaded | 3243 | | Retweets | 579 | | Short tweets | 62 | | Tweets kept | 2602 | [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1hp88bd4/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 @redo's tweets. Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3ncfpyxs) for full transparency and reproducibility. At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3ncfpyxs/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/redo') 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)
jonatasgrosman/exp_w2v2t_it_vp-nl_s27
0677593b3ef62b0b405af36e746fd59af0ea136f
2022-07-08T20:51:06.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-nl_s27
2
null
transformers
26,730
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-nl_s27 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-nl_s222
da53bcf94ee904e11a98965a6aaf55890561644e
2022-07-08T20:54:30.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-nl_s222
2
null
transformers
26,731
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-nl_s222 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-nl_s335
980e324a760e42ee231f02976960f40224529df7
2022-07-08T20:58:20.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-nl_s335
2
null
transformers
26,732
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-nl_s335 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s500
60afae3a1027380a8be50699307eadfa341ac386
2022-07-08T21:10:22.000Z
[ "pytorch", "unispeech-sat", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s500
2
null
transformers
26,733
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_unispeech-sat_s500 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s306
7eb6122ea76c6130bb33c8dc2649372b4d63ea62
2022-07-08T21:48:04.000Z
[ "pytorch", "unispeech-sat", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s306
2
null
transformers
26,734
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_unispeech-sat_s306 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s692
cfc5ff6c6e2c81056d398919afce7324d2e2dbed
2022-07-08T21:56:35.000Z
[ "pytorch", "unispeech-sat", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s692
2
null
transformers
26,735
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_unispeech-sat_s692 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_xls-r_s417
43b5d97a2e0f29a36bad5c30ed2196dce43722fb
2022-07-08T22:22:06.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_xls-r_s417
2
null
transformers
26,736
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_xls-r_s417 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 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_xls-r_s226
5eef06e6df547a55e4beb633c2d4bcfbc60c5888
2022-07-08T22:28:27.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_xls-r_s226
2
null
transformers
26,737
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_xls-r_s226 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 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_xls-r_s156
0de093bf53ff7829124a9a55a2819f9c2a190119
2022-07-08T22:33:51.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_xls-r_s156
2
null
transformers
26,738
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_xls-r_s156 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 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s317
8a0b587733d6bb9f2de8a72d3457123a56083326
2022-07-08T22:37:57.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s317
2
null
transformers
26,739
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_r-wav2vec2_s317 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s646
8cfd419f750d876786283e0a33c6dce2c4ed3497
2022-07-08T22:41:20.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s646
2
null
transformers
26,740
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_r-wav2vec2_s646 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s578
160b7d385a4ca4a42c1da9171fae1f88330d0feb
2022-07-08T22:44:54.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s578
2
null
transformers
26,741
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_r-wav2vec2_s578 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-it_s324
a775b71cfc3db0596d7b2430398e82a6f74ff65c
2022-07-08T22:48:14.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-it_s324
2
null
transformers
26,742
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-it_s324 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-it_s411
7bb0a26dfc637b02ccfbb03b7086e035f669b771
2022-07-08T22:51:42.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-it_s411
2
null
transformers
26,743
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-it_s411 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_it_vp-it_s965
ab60c0b44b0342ce6a0609ef3b1d11f64c328306
2022-07-08T22:55:05.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "it", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_it_vp-it_s965
2
null
transformers
26,744
--- language: - it license: apache-2.0 tags: - automatic-speech-recognition - it datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_it_vp-it_s965 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_fr_vp-fr_s438
0048d545718140690d6aad311a8dd5ab52335b49
2022-07-09T01:03:57.000Z
[ "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_w2v2t_fr_vp-fr_s438
2
null
transformers
26,745
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_vp-fr_s438 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_vp-fr_s179
a547076c0cf09a0a6c01ed16c57aaf85fb6d1f59
2022-07-09T01:07:16.000Z
[ "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_w2v2t_fr_vp-fr_s179
2
null
transformers
26,746
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_vp-fr_s179 Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_vp-es_s169
3a865415343bc81da8d1860abe6f59b965b70d5a
2022-07-09T01:10:31.000Z
[ "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_w2v2t_fr_vp-es_s169
2
null
transformers
26,747
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_vp-es_s169 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_vp-es_s281
c919aa13ca7b533bfc2ed4a83fa2c59596238745
2022-07-09T01:13:47.000Z
[ "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_w2v2t_fr_vp-es_s281
2
null
transformers
26,748
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_vp-es_s281 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_vp-es_s980
b6a692fe04646dcce0a19ec10046125f4e04f5cc
2022-07-09T01:17:07.000Z
[ "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_w2v2t_fr_vp-es_s980
2
null
transformers
26,749
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_vp-es_s980 Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_vp-nl_s863
cf228355e61a87cfe8ca1e86403d7b60690368a2
2022-07-09T01:20:23.000Z
[ "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_w2v2t_fr_vp-nl_s863
2
null
transformers
26,750
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_vp-nl_s863 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_vp-nl_s93
c540aabd184130c7126eb1b3b1ea716e9b7d9013
2022-07-09T01:23:53.000Z
[ "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_w2v2t_fr_vp-nl_s93
2
null
transformers
26,751
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_vp-nl_s93 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_vp-nl_s44
900ab7b0e6d62908fd2c022d10516dfb062c5370
2022-07-09T01:27:14.000Z
[ "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_w2v2t_fr_vp-nl_s44
2
null
transformers
26,752
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_vp-nl_s44 Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_unispeech-sat_s655
d876baeb3923982188036c036cf5d22bf4acbce7
2022-07-09T01:30:33.000Z
[ "pytorch", "unispeech-sat", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_fr_unispeech-sat_s655
2
null
transformers
26,753
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_unispeech-sat_s655 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_unispeech-sat_s115
90066e0f759e213769cc7ae52b1b0dc26bd3153f
2022-07-09T01:33:39.000Z
[ "pytorch", "unispeech-sat", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_fr_unispeech-sat_s115
2
null
transformers
26,754
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_unispeech-sat_s115 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_unispeech-sat_s26
7bf7b1d986b9d3ba7d3e1f406306f0d15d85f70d
2022-07-09T01:36:57.000Z
[ "pytorch", "unispeech-sat", "automatic-speech-recognition", "fr", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_fr_unispeech-sat_s26
2
null
transformers
26,755
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_unispeech-sat_s26 Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_xls-r_s515
bd11242f1b4fcb0f3f28b1f61959776a325d3811
2022-07-09T01:40:22.000Z
[ "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_w2v2t_fr_xls-r_s515
2
null
transformers
26,756
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_xls-r_s515 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_w2v2t_fr_xls-r_s250
fced91821a14eebe0b7fe9609407f95e5b2ed74c
2022-07-09T01:43:44.000Z
[ "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_w2v2t_fr_xls-r_s250
2
null
transformers
26,757
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_xls-r_s250 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_w2v2t_fr_xls-r_s859
529abcccb31b327648bf6197898fdd1d634b6dcf
2022-07-09T01:47:09.000Z
[ "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_w2v2t_fr_xls-r_s859
2
null
transformers
26,758
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_xls-r_s859 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_w2v2t_fr_r-wav2vec2_s456
7c0c0f41b3d562a59fda81b9f71a0687a3435518
2022-07-09T01:50:41.000Z
[ "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_w2v2t_fr_r-wav2vec2_s456
2
null
transformers
26,759
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_r-wav2vec2_s456 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_r-wav2vec2_s251
a277c4ac5e3e1e2511caace77e52189f6b2ac34e
2022-07-09T01:54:18.000Z
[ "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_w2v2t_fr_r-wav2vec2_s251
2
null
transformers
26,760
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_r-wav2vec2_s251 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_r-wav2vec2_s459
773d1d99f2ab1d4eb1de8657441a94dfb750b4b1
2022-07-09T01:57:35.000Z
[ "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_w2v2t_fr_r-wav2vec2_s459
2
null
transformers
26,761
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_r-wav2vec2_s459 Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_vp-it_s878
38426a406538d2c31350ebfc65e77d54223f5cb1
2022-07-09T02:00:45.000Z
[ "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_w2v2t_fr_vp-it_s878
2
null
transformers
26,762
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_vp-it_s878 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (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_w2v2t_fr_vp-it_s203
de7be11480c495ec59a1b91ae0d48ce914d3bf99
2022-07-09T02:04:23.000Z
[ "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_w2v2t_fr_vp-it_s203
2
null
transformers
26,763
--- language: - fr license: apache-2.0 tags: - automatic-speech-recognition - fr datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_fr_vp-it_s203 Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (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.
okite97/xlm-roberta-base-finetune-panx-de
a7695d9511ca28b37f5d680c2320c352b788bcd0
2022-07-09T02:30:05.000Z
[ "pytorch", "tensorboard", "xlm-roberta", "token-classification", "dataset:xtreme", "transformers", "generated_from_trainer", "license:mit", "model-index", "autotrain_compatible" ]
token-classification
false
okite97
null
okite97/xlm-roberta-base-finetune-panx-de
2
null
transformers
26,764
--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetune-panx-de results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme args: PAN-X.de metrics: - name: F1 type: f1 value: 0.8611443210930829 --- <!-- 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. --> # xlm-roberta-base-finetune-panx-de This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset. It achieves the following results on the evaluation set: - Loss: 0.1405 - F1: 0.8611 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.2542 | 1.0 | 787 | 0.1788 | 0.8083 | | 0.1307 | 2.0 | 1574 | 0.1371 | 0.8488 | | 0.0784 | 3.0 | 2361 | 0.1405 | 0.8611 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1
okite97/xlm-roberta-base-finetuned-panx-de-fr
97ed8a35613950bd68c02dad316e4ed5409ae627
2022-07-09T03:10:18.000Z
[ "pytorch", "xlm-roberta", "token-classification", "transformers", "generated_from_trainer", "license:mit", "model-index", "autotrain_compatible" ]
token-classification
false
okite97
null
okite97/xlm-roberta-base-finetuned-panx-de-fr
2
null
transformers
26,765
--- license: mit tags: - generated_from_trainer metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-de-fr 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. --> # xlm-roberta-base-finetuned-panx-de-fr This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1196 - F1: 0.8973 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.2837 | 1.0 | 1073 | 0.1775 | 0.8379 | | 0.1446 | 2.0 | 2146 | 0.1301 | 0.8767 | | 0.0917 | 3.0 | 3219 | 0.1196 | 0.8973 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1
okite97/xlm-roberta-base-finetuned-panx-fr
90d496532f89dcb35ba71589e18e08b6e3e825b1
2022-07-09T03:29:41.000Z
[ "pytorch", "xlm-roberta", "token-classification", "dataset:xtreme", "transformers", "generated_from_trainer", "license:mit", "model-index", "autotrain_compatible" ]
token-classification
false
okite97
null
okite97/xlm-roberta-base-finetuned-panx-fr
2
null
transformers
26,766
--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-fr results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme args: PAN-X.fr metrics: - name: F1 type: f1 value: 0.809109176155392 --- <!-- 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. --> # xlm-roberta-base-finetuned-panx-fr This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset. It achieves the following results on the evaluation set: - Loss: 0.3390 - F1: 0.8091 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.6995 | 1.0 | 144 | 0.3922 | 0.7317 | | 0.3222 | 2.0 | 288 | 0.3372 | 0.7958 | | 0.208 | 3.0 | 432 | 0.3390 | 0.8091 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1
okite97/xlm-roberta-base-finetuned-panx-it
26cc6a3a53b2bb10ae025a67b4cb330fdc5bf311
2022-07-09T03:46:31.000Z
[ "pytorch", "xlm-roberta", "token-classification", "dataset:xtreme", "transformers", "generated_from_trainer", "license:mit", "model-index", "autotrain_compatible" ]
token-classification
false
okite97
null
okite97/xlm-roberta-base-finetuned-panx-it
2
null
transformers
26,767
--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-it results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme args: PAN-X.it metrics: - name: F1 type: f1 value: 0.8289473684210525 --- <!-- 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. --> # xlm-roberta-base-finetuned-panx-it This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset. It achieves the following results on the evaluation set: - Loss: 0.2403 - F1: 0.8289 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.668 | 1.0 | 105 | 0.2886 | 0.7818 | | 0.2583 | 2.0 | 210 | 0.2421 | 0.8202 | | 0.1682 | 3.0 | 315 | 0.2403 | 0.8289 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1
okite97/xlm-roberta-base-finetuned-panx-en
d5d6b64d6d89b091e42f46e21dbe11c54ecfb7fc
2022-07-09T04:03:37.000Z
[ "pytorch", "xlm-roberta", "token-classification", "dataset:xtreme", "transformers", "generated_from_trainer", "license:mit", "model-index", "autotrain_compatible" ]
token-classification
false
okite97
null
okite97/xlm-roberta-base-finetuned-panx-en
2
null
transformers
26,768
--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-en results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme args: PAN-X.en metrics: - name: F1 type: f1 value: 0.6994475138121546 --- <!-- 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. --> # xlm-roberta-base-finetuned-panx-en This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset. It achieves the following results on the evaluation set: - Loss: 0.3848 - F1: 0.6994 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 1.0435 | 1.0 | 74 | 0.5169 | 0.5532 | | 0.4719 | 2.0 | 148 | 0.4224 | 0.6630 | | 0.3424 | 3.0 | 222 | 0.3848 | 0.6994 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1
okite97/xlm-roberta-base-finetuned-panx-all
1bc0865670bfc6e641b6682aa47cdb621d0dd620
2022-07-09T04:33:41.000Z
[ "pytorch", "xlm-roberta", "token-classification", "transformers", "generated_from_trainer", "license:mit", "model-index", "autotrain_compatible" ]
token-classification
false
okite97
null
okite97/xlm-roberta-base-finetuned-panx-all
2
null
transformers
26,769
--- license: mit tags: - generated_from_trainer metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-all 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. --> # xlm-roberta-base-finetuned-panx-all This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1883 - F1: 0.8538 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.2967 | 1.0 | 1109 | 0.2050 | 0.8180 | | 0.1571 | 2.0 | 2218 | 0.1880 | 0.8415 | | 0.0983 | 3.0 | 3327 | 0.1883 | 0.8538 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s451
576c41e8f8ae6316a410b174b05cb841d857b87e
2022-07-09T13:41:24.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s451
2
null
transformers
26,770
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_wav2vec2_s451 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s818
c7dc11e00a14e3e5c8c02591b95de40665645401
2022-07-09T14:06:26.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s818
2
null
transformers
26,771
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_wav2vec2_s818 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s732
985447570c91ffdc99bc5cd2e9b7eb077689fac5
2022-07-09T14:33:48.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s732
2
null
transformers
26,772
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_wav2vec2_s732 Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s108
983eee09088e95fa68b03061cc67762c8b502959
2022-07-09T15:01:41.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s108
2
null
transformers
26,773
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_vp-100k_s108 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s904
cb264fb4b8d5062d50a30d3c574c47c7d53f7425
2022-07-09T15:16:59.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s904
2
null
transformers
26,774
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_vp-100k_s904 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](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.
huangjia/xlm-roberta-base-finetuned-panx-de
f69700072620892b96db3675aaf52f0f4eb1a0ed
2022-07-09T15:39:43.000Z
[ "pytorch", "tensorboard", "xlm-roberta", "token-classification", "dataset:xtreme", "transformers", "generated_from_trainer", "license:mit", "model-index", "autotrain_compatible" ]
token-classification
false
huangjia
null
huangjia/xlm-roberta-base-finetuned-panx-de
2
null
transformers
26,775
--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-de results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme args: PAN-X.de metrics: - name: F1 type: f1 value: 0.8550872422388397 --- <!-- 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. --> # xlm-roberta-base-finetuned-panx-de This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset. It achieves the following results on the evaluation set: - Loss: 0.1333 - F1: 0.8551 ## 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: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 1.0 | 263 | 0.1573 | 0.8137 | | 0.2142 | 2.0 | 526 | 0.1386 | 0.8466 | | 0.2142 | 3.0 | 789 | 0.1333 | 0.8551 | ### Framework versions - Transformers 4.11.3 - Pytorch 1.10.2 - Datasets 1.18.4 - Tokenizers 0.10.3
huangjia/xlm-roberta-base-finetuned-panx-de-fr
db938cf5a89b647be1ca3ee6ebfe1f4c88b7f24c
2022-07-09T15:58:43.000Z
[ "pytorch", "xlm-roberta", "token-classification", "transformers", "generated_from_trainer", "license:mit", "model-index", "autotrain_compatible" ]
token-classification
false
huangjia
null
huangjia/xlm-roberta-base-finetuned-panx-de-fr
2
null
transformers
26,776
--- license: mit tags: - generated_from_trainer metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-de-fr 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. --> # xlm-roberta-base-finetuned-panx-de-fr This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1584 - F1: 0.8537 ## 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: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 1.0 | 358 | 0.1776 | 0.8263 | | 0.2394 | 2.0 | 716 | 0.1599 | 0.8447 | | 0.2394 | 3.0 | 1074 | 0.1584 | 0.8537 | ### Framework versions - Transformers 4.11.3 - Pytorch 1.10.2 - Datasets 1.18.4 - Tokenizers 0.10.3
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s847
6bc2933e3372fb5f4fbd578b7af9ff380cc83b83
2022-07-09T15:48:44.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s847
2
null
transformers
26,777
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_vp-100k_s847 Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s328
4d5c85d839f55c101857ab2cbf4aaf5fb3e7e974
2022-07-09T15:52:26.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s328
2
null
transformers
26,778
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_xlsr-53_s328 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s131
5b200e7d5046022fcc7ae3773b39deb562a9c8d0
2022-07-09T15:56:30.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s131
2
null
transformers
26,779
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_xlsr-53_s131 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s624
9ee84e5ec4459b37743b2a578dbb5af4e635f725
2022-07-09T16:00:26.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s624
2
null
transformers
26,780
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_xlsr-53_s624 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](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.
huangjia/xlm-roberta-base-finetuned-panx-fr
93a814a2fe4f97af3c595cf44173629ca64bb039
2022-07-09T16:05:20.000Z
[ "pytorch", "xlm-roberta", "token-classification", "dataset:xtreme", "transformers", "generated_from_trainer", "license:mit", "model-index", "autotrain_compatible" ]
token-classification
false
huangjia
null
huangjia/xlm-roberta-base-finetuned-panx-fr
2
null
transformers
26,781
--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-fr results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme args: PAN-X.fr metrics: - name: F1 type: f1 value: 0.8204272363150867 --- <!-- 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. --> # xlm-roberta-base-finetuned-panx-fr This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset. It achieves the following results on the evaluation set: - Loss: 0.2739 - F1: 0.8204 ## 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: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 1.0 | 96 | 0.3708 | 0.7672 | | 0.506 | 2.0 | 192 | 0.2967 | 0.8130 | | 0.506 | 3.0 | 288 | 0.2739 | 0.8204 | ### Framework versions - Transformers 4.11.3 - Pytorch 1.10.2 - Datasets 1.18.4 - Tokenizers 0.10.3
huangjia/xlm-roberta-base-finetuned-panx-it
4b35a8a06e5b05efa9e29f18125689f1d34b88d4
2022-07-09T16:09:16.000Z
[ "pytorch", "xlm-roberta", "token-classification", "dataset:xtreme", "transformers", "generated_from_trainer", "license:mit", "model-index", "autotrain_compatible" ]
token-classification
false
huangjia
null
huangjia/xlm-roberta-base-finetuned-panx-it
2
null
transformers
26,782
--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-it results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme args: PAN-X.it metrics: - name: F1 type: f1 value: 0.7938060309698453 --- <!-- 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. --> # xlm-roberta-base-finetuned-panx-it This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset. It achieves the following results on the evaluation set: - Loss: 0.2687 - F1: 0.7938 ## 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: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 1.0 | 35 | 0.4625 | 0.6674 | | 0.7337 | 2.0 | 70 | 0.3035 | 0.7613 | | 0.7337 | 3.0 | 105 | 0.2687 | 0.7938 | ### Framework versions - Transformers 4.11.3 - Pytorch 1.10.2 - Datasets 1.18.4 - Tokenizers 0.10.3
huangjia/xlm-roberta-base-finetuned-panx-all
19cfa84d0da22407b2d9b7ae0bbb3aef52547aa6
2022-07-09T16:25:28.000Z
[ "pytorch", "xlm-roberta", "token-classification", "transformers", "generated_from_trainer", "license:mit", "model-index", "autotrain_compatible" ]
token-classification
false
huangjia
null
huangjia/xlm-roberta-base-finetuned-panx-all
2
null
transformers
26,783
--- license: mit tags: - generated_from_trainer metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-all 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. --> # xlm-roberta-base-finetuned-panx-all This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1709 - F1: 0.8561 ## 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: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 1.0 | 418 | 0.2042 | 0.8064 | | 0.2421 | 2.0 | 836 | 0.1773 | 0.8376 | | 0.2421 | 3.0 | 1254 | 0.1709 | 0.8561 | ### Framework versions - Transformers 4.11.3 - Pytorch 1.10.2 - Datasets 1.18.4 - Tokenizers 0.10.3
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s149
cca43c32031d3248c3c4ecc5f509295a889b95c3
2022-07-09T16:18:55.000Z
[ "pytorch", "unispeech", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s149
2
null
transformers
26,784
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_unispeech_s149 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s449
d7d4a0f5f47abd4fd77b5a551f98ab941f580724
2022-07-09T16:30:10.000Z
[ "pytorch", "unispeech", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s449
2
null
transformers
26,785
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_unispeech_s449 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s358
d7327ba3ca79551f26d80203a11dac096c1ad0fe
2022-07-09T16:37:28.000Z
[ "pytorch", "unispeech", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s358
2
null
transformers
26,786
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_unispeech_s358 Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_hubert_s805
f5ffae54ba92d6a565d6027ef855b8dd85c161db
2022-07-09T16:45:49.000Z
[ "pytorch", "hubert", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_hubert_s805
2
null
transformers
26,787
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_hubert_s805 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_hubert_s730
9c14b96f8db661000edd496a29b8e86f45942ad1
2022-07-09T16:53:37.000Z
[ "pytorch", "hubert", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_hubert_s730
2
null
transformers
26,788
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_hubert_s730 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_hubert_s930
beaa1908ecf26a40afcaffdf877bd4fcfd1b90ca
2022-07-09T16:58:31.000Z
[ "pytorch", "hubert", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_hubert_s930
2
null
transformers
26,789
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_hubert_s930 Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s363
0c2a76da879be965e2dcdf98a0cdd5e5a5b2f12e
2022-07-09T17:05:30.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s363
2
null
transformers
26,790
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_vp-sv_s363 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s331
583c621de07e288cfe7689a0374081633e09a8a4
2022-07-09T17:20:04.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s331
2
null
transformers
26,791
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_vp-sv_s331 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s116
f3b51162eadc454c167ee9fbcb271b5dc3b0db85
2022-07-09T17:27:31.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s116
2
null
transformers
26,792
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_vp-sv_s116 Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s910
7dc449ca3f2a699c63aa7e5c3784bb93fe43be61
2022-07-09T17:30:44.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s910
2
null
transformers
26,793
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_no-pretraining_s910 Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s705
1c5331f8041d1b170757ad4a77ea1e4401d914c9
2022-07-09T17:33:54.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s705
2
null
transformers
26,794
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_no-pretraining_s705 Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s630
b4319b63dce12122a3a6bdce13c2f33afec6e8f4
2022-07-09T17:37:13.000Z
[ "pytorch", "wav2vec2", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s630
2
null
transformers
26,795
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_no-pretraining_s630 Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s132
2bb4cace8906467d4d13ed1fa7dfb69ea6eddffb
2022-07-09T17:40:35.000Z
[ "pytorch", "wavlm", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s132
2
null
transformers
26,796
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_wavlm_s132 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s42
3be6432c00778eecd9c410d3179d542df9e93e17
2022-07-09T17:44:00.000Z
[ "pytorch", "wavlm", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s42
2
null
transformers
26,797
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_wavlm_s42 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s607
d46f6989127a8a593469ac8c987d11d3f692a68f
2022-07-09T17:47:17.000Z
[ "pytorch", "wavlm", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s607
2
null
transformers
26,798
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_wavlm_s607 Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s35
39886766cef5f5b9f2ccd3dbf84bfa2a0f453839
2022-07-09T17:50:40.000Z
[ "pytorch", "unispeech", "automatic-speech-recognition", "sv-SE", "dataset:mozilla-foundation/common_voice_7_0", "transformers", "license:apache-2.0" ]
automatic-speech-recognition
false
jonatasgrosman
null
jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s35
2
null
transformers
26,799
--- language: - sv-SE license: apache-2.0 tags: - automatic-speech-recognition - sv-SE datasets: - mozilla-foundation/common_voice_7_0 --- # exp_w2v2t_sv-se_unispeech-ml_s35 Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](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.