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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-combined-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-combined-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: 0.3149 |
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- Wer: 0.3760 |
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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: 30.0 |
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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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| 15.204 | 0.4474 | 100 | 3.5867 | 1.0672 | |
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| 4.2355 | 0.8949 | 200 | 0.5745 | 0.5648 | |
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| 1.4309 | 1.3400 | 300 | 0.4451 | 0.5084 | |
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| 1.1797 | 1.7875 | 400 | 0.4035 | 0.4828 | |
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| 1.1218 | 2.2327 | 500 | 0.3912 | 0.4663 | |
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| 1.0287 | 2.6801 | 600 | 0.3838 | 0.4552 | |
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| 0.9773 | 3.1253 | 700 | 0.3751 | 0.4481 | |
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| 1.038 | 3.5727 | 800 | 0.3665 | 0.4421 | |
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| 0.9878 | 4.0179 | 900 | 0.3571 | 0.4356 | |
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| 0.9888 | 4.4653 | 1000 | 0.3510 | 0.4359 | |
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| 0.8904 | 4.9128 | 1100 | 0.3498 | 0.4172 | |
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| 0.8178 | 5.3579 | 1200 | 0.3456 | 0.4152 | |
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| 0.9608 | 5.8054 | 1300 | 0.3384 | 0.4184 | |
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| 0.9166 | 6.2506 | 1400 | 0.3416 | 0.4099 | |
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| 0.8623 | 6.6980 | 1500 | 0.3351 | 0.4034 | |
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| 0.823 | 7.1432 | 1600 | 0.3306 | 0.3977 | |
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| 0.8495 | 7.5906 | 1700 | 0.3321 | 0.3937 | |
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| 0.8691 | 8.0358 | 1800 | 0.3244 | 0.3986 | |
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| 0.8225 | 8.4832 | 1900 | 0.3261 | 0.3956 | |
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| 0.8193 | 8.9306 | 2000 | 0.3224 | 0.3921 | |
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| 0.79 | 9.3758 | 2100 | 0.3181 | 0.3884 | |
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| 0.8035 | 9.8233 | 2200 | 0.3272 | 0.3887 | |
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| 0.8391 | 10.2685 | 2300 | 0.3177 | 0.3894 | |
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| 0.8055 | 10.7159 | 2400 | 0.3255 | 0.3790 | |
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| 0.7124 | 11.1611 | 2500 | 0.3137 | 0.3912 | |
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| 0.7747 | 11.6085 | 2600 | 0.3264 | 0.3850 | |
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| 0.795 | 12.0537 | 2700 | 0.3150 | 0.3852 | |
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| 0.7749 | 12.5011 | 2800 | 0.3177 | 0.3806 | |
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| 0.7364 | 12.9485 | 2900 | 0.3150 | 0.3762 | |
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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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