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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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- mozilla-foundation/common_voice_7_0 |
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- generated_from_trainer |
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- robust-speech-event |
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model-index: |
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- name: XLS-R-300M - French |
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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: Common Voice 7 |
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type: mozilla-foundation/common_voice_7_0 |
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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: 24.56 |
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- name: Test CER |
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type: cer |
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value: 7.3 |
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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_7_0 - FR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2619 |
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- Wer: 0.2457 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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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: 2.0 |
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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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| 3.495 | 0.16 | 500 | 3.3883 | 1.0 | |
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| 2.9095 | 0.32 | 1000 | 2.9152 | 1.0000 | |
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| 1.8434 | 0.49 | 1500 | 1.0473 | 0.7446 | |
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| 1.4298 | 0.65 | 2000 | 0.5729 | 0.5130 | |
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| 1.1937 | 0.81 | 2500 | 0.3795 | 0.3450 | |
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| 1.1248 | 0.97 | 3000 | 0.3321 | 0.3052 | |
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| 1.0835 | 1.13 | 3500 | 0.3038 | 0.2805 | |
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| 1.0479 | 1.3 | 4000 | 0.2910 | 0.2689 | |
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| 1.0413 | 1.46 | 4500 | 0.2798 | 0.2593 | |
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| 1.014 | 1.62 | 5000 | 0.2727 | 0.2512 | |
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| 1.004 | 1.78 | 5500 | 0.2646 | 0.2471 | |
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| 0.9949 | 1.94 | 6000 | 0.2619 | 0.2457 | |
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### Eval results on Common Voice 7 "test" (WER): |
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| Without LM | With LM | |
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|---|---| |
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| 24.56 | To be computed | |
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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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