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--- |
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language: |
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- mr |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- mozilla-foundation/common_voice_8_0 |
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- mr |
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- robust-speech-event |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: '' |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: Common Voice Corpus 8.0 |
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type: mozilla-foundation/common_voice_8_0 |
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args: mr |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 38.27 |
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- name: Test CER |
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type: cer |
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value: 8.91 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MR dataset. |
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It achieves the following results on the mozilla-foundation/common_voice_8_0 mr test set: |
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- Without LM |
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+ WER: 48.53 |
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+ CER: 10.63 |
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- With LM |
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+ WER: 38.27 |
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+ CER: 8.91 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 7.5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 2000 |
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- num_epochs: 400.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 4.2706 | 22.73 | 500 | 4.0174 | 1.0 | |
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| 3.2492 | 45.45 | 1000 | 3.2309 | 0.9908 | |
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| 1.9709 | 68.18 | 1500 | 1.0651 | 0.8440 | |
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| 1.4088 | 90.91 | 2000 | 0.5765 | 0.6550 | |
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| 1.1326 | 113.64 | 2500 | 0.4842 | 0.5760 | |
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| 0.9709 | 136.36 | 3000 | 0.4785 | 0.6013 | |
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| 0.8433 | 159.09 | 3500 | 0.5048 | 0.5419 | |
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| 0.7404 | 181.82 | 4000 | 0.5052 | 0.5339 | |
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| 0.6589 | 204.55 | 4500 | 0.5237 | 0.5897 | |
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| 0.5831 | 227.27 | 5000 | 0.5166 | 0.5447 | |
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| 0.5375 | 250.0 | 5500 | 0.5292 | 0.5487 | |
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| 0.4784 | 272.73 | 6000 | 0.5480 | 0.5596 | |
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| 0.4421 | 295.45 | 6500 | 0.5682 | 0.5467 | |
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| 0.4047 | 318.18 | 7000 | 0.5681 | 0.5447 | |
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| 0.3779 | 340.91 | 7500 | 0.5783 | 0.5347 | |
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| 0.3525 | 363.64 | 8000 | 0.5856 | 0.5367 | |
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| 0.3393 | 386.36 | 8500 | 0.5960 | 0.5359 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu113 |
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- Datasets 1.18.1.dev0 |
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- Tokenizers 0.11.0 |
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