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--- |
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license: apache-2.0 |
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language: |
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- vi |
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tags: |
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- automatic-speech-recognition |
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- robust-speech-event |
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- common-voice |
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- vi |
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model-index: |
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- name: wav2vec2-large-xlsr-53-ja |
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results: |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 8.0 |
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type: mozilla-foundation/common_voice_8_0 |
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args: ja |
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metrics: |
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- name: Test WER (with LM) |
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type: wer |
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value: 16.08 |
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- name: Test CER (with LM) |
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type: cer |
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value: 7.15 |
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--- |
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## Model description |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA dataset. |
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### Benchmark WER result: |
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| | [COMMON VOICE 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) | [COMMON VOICE 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0) |
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|---|---|---| |
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|without LM| 15.74 | 25.10 | |
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|with 4-grams LM| 15.37 | 16.09 | |
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### Benchmark CER result: |
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| | [COMMON VOICE 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) | [COMMON VOICE 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0) |
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|---|---|---| |
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|without LM| 9.51 | 9.95 | |
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|with 4-grams LM| 6.91 | 7.15 | |
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## Evaluation |
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Please use the eval.py file to run the evaluation: |
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```python |
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python eval.py --model_id vutankiet2901/wav2vec2-large-xlsr-53-ja --dataset mozilla-foundation/common_voice_7_0 --config ja --split test --log_outputs |
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``` |
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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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- gradient_accumulation_steps: 2 |
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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: 50.0 |
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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 | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 4.7776 | 4.73 | 1500 | 2.9540 | 0.9772 | 0.8489 | |
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| 1.9076 | 9.46 | 3000 | 0.7146 | 0.5371 | 0.2484 | |
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| 1.507 | 14.2 | 4500 | 0.5843 | 0.4689 | 0.2196 | |
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| 1.3742 | 18.93 | 6000 | 0.5286 | 0.4321 | 0.1988 | |
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| 1.2776 | 23.66 | 7500 | 0.5007 | 0.4056 | 0.1870 | |
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| 1.2003 | 28.39 | 9000 | 0.4676 | 0.3848 | 0.1802 | |
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| 1.1281 | 33.12 | 10500 | 0.4524 | 0.3694 | 0.1720 | |
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| 1.0657 | 37.85 | 12000 | 0.4449 | 0.3590 | 0.1681 | |
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| 1.0129 | 42.59 | 13500 | 0.4266 | 0.3423 | 0.1617 | |
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| 0.9691 | 47.32 | 15000 | 0.4214 | 0.3375 | 0.1587 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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