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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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- toigen |
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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-toigen-balanced-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-toigen-balanced-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 TOIGEN - TOI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3234 |
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- Wer: 0.3755 |
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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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- num_epochs: 2500.0 |
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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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| 14.2297 | 0.8850 | 100 | 3.4836 | 1.0056 | |
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| 4.1389 | 1.7699 | 200 | 0.5562 | 0.5694 | |
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| 1.3643 | 2.6549 | 300 | 0.4360 | 0.4958 | |
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| 1.1715 | 3.5398 | 400 | 0.3980 | 0.4824 | |
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| 1.1309 | 4.4248 | 500 | 0.3785 | 0.4583 | |
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| 1.0283 | 5.3097 | 600 | 0.3741 | 0.4477 | |
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| 1.0148 | 6.1947 | 700 | 0.3669 | 0.4403 | |
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| 0.9961 | 7.0796 | 800 | 0.3607 | 0.4356 | |
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| 0.9248 | 7.9646 | 900 | 0.3581 | 0.4236 | |
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| 0.9482 | 8.8496 | 1000 | 0.3463 | 0.4356 | |
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| 0.8815 | 9.7345 | 1100 | 0.3488 | 0.4273 | |
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| 0.8209 | 10.6195 | 1200 | 0.3384 | 0.4 | |
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| 0.8754 | 11.5044 | 1300 | 0.3459 | 0.4051 | |
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| 0.8454 | 12.3894 | 1400 | 0.3317 | 0.3884 | |
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| 0.8164 | 13.2743 | 1500 | 0.3319 | 0.4032 | |
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| 0.7673 | 14.1593 | 1600 | 0.3311 | 0.3921 | |
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| 0.7953 | 15.0442 | 1700 | 0.3333 | 0.3944 | |
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| 0.7527 | 15.9292 | 1800 | 0.3313 | 0.3917 | |
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| 0.763 | 16.8142 | 1900 | 0.3278 | 0.3931 | |
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| 0.7319 | 17.6991 | 2000 | 0.3234 | 0.3755 | |
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| 0.7352 | 18.5841 | 2100 | 0.3248 | 0.3806 | |
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| 0.7017 | 19.4690 | 2200 | 0.3334 | 0.3852 | |
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| 0.6902 | 20.3540 | 2300 | 0.3304 | 0.3889 | |
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| 0.707 | 21.2389 | 2400 | 0.3314 | 0.3856 | |
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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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