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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- automatic-speech-recognition |
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- bigcgen |
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- mms |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: mms-1b-bigcgen-combined-20hrs-model |
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results: [] |
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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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# mms-1b-bigcgen-combined-20hrs-model |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the BIGCGEN - BEM dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: inf |
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- Wer: 0.5166 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 2500 |
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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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| 14.8448 | 0.0762 | 100 | inf | 1.0079 | |
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| 6.2506 | 0.1524 | 200 | inf | 1.0042 | |
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| 5.5314 | 0.2287 | 300 | inf | 1.0270 | |
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| 3.4418 | 0.3049 | 400 | inf | 0.5906 | |
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| 1.9396 | 0.3811 | 500 | inf | 0.5762 | |
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| 1.698 | 0.4573 | 600 | inf | 0.5566 | |
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| 1.5483 | 0.5335 | 700 | inf | 0.5571 | |
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| 1.6501 | 0.6098 | 800 | inf | 0.5487 | |
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| 1.5528 | 0.6860 | 900 | inf | 0.5471 | |
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| 1.5398 | 0.7622 | 1000 | inf | 0.5479 | |
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| 1.6413 | 0.8384 | 1100 | inf | 0.5304 | |
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| 1.418 | 0.9146 | 1200 | inf | 0.5283 | |
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| 1.5625 | 0.9909 | 1300 | inf | 0.5265 | |
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| 1.4753 | 1.0671 | 1400 | inf | 0.5347 | |
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| 1.616 | 1.1433 | 1500 | inf | 0.5309 | |
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| 1.3802 | 1.2195 | 1600 | inf | 0.5246 | |
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| 1.4105 | 1.2957 | 1700 | inf | 0.5197 | |
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| 1.3793 | 1.3720 | 1800 | inf | 0.5288 | |
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| 1.3991 | 1.4482 | 1900 | inf | 0.5140 | |
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| 1.5838 | 1.5244 | 2000 | inf | 0.5239 | |
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| 1.6283 | 1.6006 | 2100 | inf | 0.5144 | |
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| 1.4131 | 1.6768 | 2200 | inf | 0.5135 | |
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| 1.388 | 1.7530 | 2300 | inf | 0.5137 | |
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| 1.3846 | 1.8293 | 2400 | inf | 0.5145 | |
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| 1.497 | 1.9055 | 2500 | inf | 0.5167 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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