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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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- 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-baseline-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-baseline-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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5130 |
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- Wer: 0.4597 |
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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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| 12.3367 | 0.3058 | 100 | 1.3241 | 0.8893 | |
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| 1.8764 | 0.6116 | 200 | 0.6894 | 0.5815 | |
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| 1.6712 | 0.9174 | 300 | 0.6390 | 0.5514 | |
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| 1.5044 | 1.2232 | 400 | 0.6301 | 0.5351 | |
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| 1.6648 | 1.5291 | 500 | 0.6076 | 0.5283 | |
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| 1.6411 | 1.8349 | 600 | 0.6073 | 0.5283 | |
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| 1.4016 | 2.1407 | 700 | 0.5994 | 0.5124 | |
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| 1.5703 | 2.4465 | 800 | 0.5997 | 0.5162 | |
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| 1.4165 | 2.7523 | 900 | 0.5850 | 0.5084 | |
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| 1.4703 | 3.0581 | 1000 | 0.5912 | 0.5127 | |
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| 1.48 | 3.3639 | 1100 | 0.5707 | 0.4999 | |
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| 1.4769 | 3.6697 | 1200 | 0.5675 | 0.4949 | |
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| 1.312 | 3.9755 | 1300 | 0.5856 | 0.4980 | |
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| 1.3821 | 4.2813 | 1400 | 0.5642 | 0.4992 | |
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| 1.457 | 4.5872 | 1500 | 0.5588 | 0.5053 | |
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| 1.3606 | 4.8930 | 1600 | 0.5637 | 0.4866 | |
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| 1.3986 | 5.1988 | 1700 | 0.5511 | 0.4866 | |
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| 1.421 | 5.5046 | 1800 | 0.5846 | 0.5346 | |
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| 1.3004 | 5.8104 | 1900 | 0.5440 | 0.4736 | |
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| 1.3319 | 6.1162 | 2000 | 0.5318 | 0.4786 | |
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| 1.2665 | 6.4220 | 2100 | 0.5488 | 0.5065 | |
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| 1.3703 | 6.7278 | 2200 | 0.5304 | 0.4878 | |
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| 1.1954 | 7.0336 | 2300 | 0.5298 | 0.4807 | |
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| 1.2973 | 7.3394 | 2400 | 0.5258 | 0.4706 | |
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| 1.2086 | 7.6453 | 2500 | 0.5231 | 0.4807 | |
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| 1.2796 | 7.9511 | 2600 | 0.5404 | 0.4739 | |
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| 1.1428 | 8.2569 | 2700 | 0.5328 | 0.4831 | |
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| 1.3118 | 8.5627 | 2800 | 0.5198 | 0.4769 | |
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| 1.2569 | 8.8685 | 2900 | 0.5306 | 0.4847 | |
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| 1.1718 | 9.1743 | 3000 | 0.5160 | 0.4649 | |
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| 1.1354 | 9.4801 | 3100 | 0.5265 | 0.4777 | |
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| 1.2795 | 9.7859 | 3200 | 0.5090 | 0.4590 | |
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| 1.1793 | 10.0917 | 3300 | 0.5265 | 0.4684 | |
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| 1.1647 | 10.3976 | 3400 | 0.5385 | 0.4762 | |
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| 1.1978 | 10.7034 | 3500 | 0.5132 | 0.4715 | |
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| 1.1802 | 11.0092 | 3600 | 0.5130 | 0.4597 | |
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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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