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--- |
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license: cc-by-nc-4.0 |
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tags: |
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- generated_from_trainer |
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base_model: utter-project/mHuBERT-147 |
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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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type: automatic-speech-recognition |
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name: 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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- type: wer |
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value: 53.76572908956329 |
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name: Wer |
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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: 0.7650 |
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- Wer: 53.7657 |
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- Cer: 18.3841 |
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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: 3.7e-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 | Cer | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:-------:|:---------------:|:-------:| |
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| 6.5746 | 2.18 | 1000 | 99.8848 | 3.8929 | 100.0 | |
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| 2.8591 | 4.36 | 2000 | 51.1549 | 1.8873 | 97.5296 | |
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| 1.4189 | 6.54 | 3000 | 27.4120 | 1.0985 | 77.2853 | |
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| 0.9787 | 8.71 | 4000 | 0.8995 | 71.3360 | 24.4590 | |
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| 0.803 | 10.89 | 5000 | 0.8429 | 67.1817 | 22.9902 | |
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| 0.718 | 13.07 | 6000 | 0.8035 | 63.8879 | 21.6750 | |
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| 0.6359 | 15.25 | 7000 | 0.7927 | 62.2502 | 21.1144 | |
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| 0.5832 | 17.43 | 8000 | 0.7508 | 60.3072 | 20.3406 | |
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| 0.555 | 19.61 | 9000 | 0.7509 | 58.7990 | 19.8568 | |
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| 0.5167 | 21.79 | 10000 | 0.7757 | 58.0218 | 19.7569 | |
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| 0.4917 | 23.97 | 11000 | 0.7588 | 56.9671 | 19.4574 | |
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| 0.4629 | 26.14 | 12000 | 0.7710 | 55.6255 | 19.0792 | |
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| 0.4454 | 28.32 | 13000 | 0.7546 | 55.0888 | 18.8257 | |
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| 0.4235 | 30.5 | 14000 | 0.7548 | 54.9963 | 18.7240 | |
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| 0.4135 | 32.68 | 15000 | 0.7689 | 54.6725 | 18.6222 | |
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| 0.411 | 34.86 | 16000 | 0.7619 | 54.4504 | 18.5320 | |
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| 0.3934 | 37.04 | 17000 | 0.7621 | 53.9323 | 18.4014 | |
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| 0.3912 | 39.22 | 18000 | 0.7650 | 53.7657 | 18.3841 | |
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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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