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--- |
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language: |
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- fr |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- common_voice |
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- fr |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- robust-speech-event |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-cls-r-300m-fr |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: fr |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 56.62 |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Robust Speech Event - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: fr |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 58.22 |
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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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# wav2vec2-cls-r-300m-fr |
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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 COMMON_VOICE - FR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6521 |
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- Wer: 0.4330 |
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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: 0.0003 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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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- num_epochs: 10.0 |
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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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| 2.6773 | 0.8 | 500 | 1.3907 | 0.9864 | |
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| 0.9526 | 1.6 | 1000 | 0.7760 | 0.6448 | |
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| 0.6418 | 2.4 | 1500 | 0.7605 | 0.6194 | |
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| 0.5028 | 3.2 | 2000 | 0.6516 | 0.5322 | |
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| 0.4133 | 4.0 | 2500 | 0.6303 | 0.5097 | |
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| 0.3285 | 4.8 | 3000 | 0.6422 | 0.5062 | |
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| 0.2764 | 5.6 | 3500 | 0.5936 | 0.4748 | |
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| 0.2361 | 6.4 | 4000 | 0.6486 | 0.4683 | |
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| 0.2049 | 7.2 | 4500 | 0.6321 | 0.4532 | |
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| 0.176 | 8.0 | 5000 | 0.6230 | 0.4482 | |
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| 0.1393 | 8.8 | 5500 | 0.6595 | 0.4403 | |
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| 0.1141 | 9.6 | 6000 | 0.6552 | 0.4348 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.2.dev0 |
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- Tokenizers 0.11.0 |
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