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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-male-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-male-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: 0.4348 |
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- Wer: 0.3988 |
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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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- 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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| 8.0084 | 0.5051 | 100 | 3.7458 | 0.9984 | |
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| 2.8136 | 1.0101 | 200 | 1.0029 | 0.7422 | |
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| 0.9647 | 1.5152 | 300 | 0.5870 | 0.5274 | |
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| 0.8539 | 2.0202 | 400 | 0.5461 | 0.5048 | |
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| 0.7525 | 2.5253 | 500 | 0.5256 | 0.4989 | |
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| 0.7307 | 3.0303 | 600 | 0.5101 | 0.4871 | |
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| 0.6997 | 3.5354 | 700 | 0.5032 | 0.4688 | |
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| 0.6882 | 4.0404 | 800 | 0.4879 | 0.4736 | |
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| 0.651 | 4.5455 | 900 | 0.4788 | 0.4559 | |
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| 0.6623 | 5.0505 | 1000 | 0.4799 | 0.4526 | |
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| 0.6339 | 5.5556 | 1100 | 0.4677 | 0.4419 | |
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| 0.6424 | 6.0606 | 1200 | 0.4650 | 0.4429 | |
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| 0.6365 | 6.5657 | 1300 | 0.4746 | 0.4462 | |
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| 0.556 | 7.0707 | 1400 | 0.4512 | 0.4381 | |
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| 0.5969 | 7.5758 | 1500 | 0.4597 | 0.4413 | |
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| 0.5772 | 8.0808 | 1600 | 0.4455 | 0.4284 | |
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| 0.5695 | 8.5859 | 1700 | 0.4565 | 0.4268 | |
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| 0.5752 | 9.0909 | 1800 | 0.4414 | 0.4187 | |
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| 0.5734 | 9.5960 | 1900 | 0.4450 | 0.4085 | |
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| 0.5465 | 10.1010 | 2000 | 0.4373 | 0.4155 | |
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| 0.5553 | 10.6061 | 2100 | 0.4520 | 0.4241 | |
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| 0.5289 | 11.1111 | 2200 | 0.4306 | 0.4085 | |
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| 0.5122 | 11.6162 | 2300 | 0.4372 | 0.4015 | |
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| 0.5659 | 12.1212 | 2400 | 0.4408 | 0.4010 | |
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| 0.5007 | 12.6263 | 2500 | 0.4274 | 0.3983 | |
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| 0.5366 | 13.1313 | 2600 | 0.4266 | 0.4026 | |
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| 0.5068 | 13.6364 | 2700 | 0.4366 | 0.3961 | |
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| 0.507 | 14.1414 | 2800 | 0.4359 | 0.3972 | |
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| 0.5031 | 14.6465 | 2900 | 0.4334 | 0.3967 | |
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| 0.4949 | 15.1515 | 3000 | 0.4348 | 0.3988 | |
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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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