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--- |
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license: cc-by-nc-4.0 |
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base_model: utter-project/mHuBERT-147 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_15_0 |
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metrics: |
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- wer |
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model-index: |
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- name: mHuBERT-147-br |
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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_15_0 |
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type: common_voice_15_0 |
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config: br |
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split: None |
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args: br |
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metrics: |
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- name: Wer |
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type: wer |
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value: 54.40414507772021 |
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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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# mHuBERT-147-br |
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This model is a fine-tuned version of [utter-project/mHuBERT-147](https://huggingface.co/utter-project/mHuBERT-147) on the common_voice_15_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7748 |
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- Wer: 54.4041 |
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- Cer: 18.4091 |
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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: 3.5e-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: 2 |
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- total_train_batch_size: 16 |
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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: 500 |
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- num_epochs: 40 |
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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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| 6.9168 | 2.18 | 1000 | 3.4435 | 100.0 | 99.8848 | |
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| 2.5187 | 4.36 | 2000 | 1.5458 | 84.7983 | 31.7071 | |
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| 1.2569 | 6.54 | 3000 | 1.0204 | 75.0740 | 26.1506 | |
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| 0.9322 | 8.71 | 4000 | 0.8765 | 69.9852 | 24.0654 | |
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| 0.785 | 10.89 | 5000 | 0.8191 | 66.0252 | 22.4968 | |
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| 0.6997 | 13.07 | 6000 | 0.8166 | 64.1007 | 21.8478 | |
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| 0.6318 | 15.25 | 7000 | 0.7961 | 61.4730 | 20.9685 | |
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| 0.5827 | 17.43 | 8000 | 0.7853 | 59.9926 | 20.2523 | |
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| 0.5573 | 19.61 | 9000 | 0.7536 | 59.6873 | 20.0737 | |
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| 0.5173 | 21.79 | 10000 | 0.7525 | 58.3364 | 19.6014 | |
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| 0.4874 | 23.97 | 11000 | 0.7694 | 57.4759 | 19.4766 | |
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| 0.4643 | 26.14 | 12000 | 0.7800 | 56.1158 | 19.0984 | |
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| 0.4511 | 28.32 | 13000 | 0.7640 | 55.6255 | 18.7892 | |
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| 0.4268 | 30.5 | 14000 | 0.7495 | 55.4404 | 18.6548 | |
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| 0.423 | 32.68 | 15000 | 0.7641 | 55.0703 | 18.5281 | |
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| 0.4166 | 34.86 | 16000 | 0.7730 | 54.8020 | 18.5377 | |
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| 0.3968 | 37.04 | 17000 | 0.7658 | 54.4597 | 18.3995 | |
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| 0.3958 | 39.22 | 18000 | 0.7748 | 54.4041 | 18.4091 | |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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