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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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- bemgen |
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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-bemgen-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-bemgen-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 BEMGEN - BEM dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2753 |
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- Wer: 0.4201 |
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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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| 6.8327 | 0.1031 | 100 | 0.8480 | 0.7889 | |
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| 0.5906 | 0.2062 | 200 | 0.3704 | 0.5819 | |
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| 0.4809 | 0.3093 | 300 | 0.3327 | 0.5039 | |
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| 0.4495 | 0.4124 | 400 | 0.3172 | 0.4894 | |
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| 0.4266 | 0.5155 | 500 | 0.3102 | 0.4632 | |
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| 0.4167 | 0.6186 | 600 | 0.3075 | 0.4716 | |
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| 0.4151 | 0.7216 | 700 | 0.2996 | 0.4829 | |
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| 0.3955 | 0.8247 | 800 | 0.2985 | 0.4712 | |
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| 0.3802 | 0.9278 | 900 | 0.2960 | 0.4926 | |
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| 0.392 | 1.0309 | 1000 | 0.2839 | 0.4374 | |
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| 0.375 | 1.1340 | 1100 | 0.2837 | 0.4318 | |
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| 0.3885 | 1.2371 | 1200 | 0.2812 | 0.4257 | |
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| 0.3824 | 1.3402 | 1300 | 0.2825 | 0.4255 | |
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| 0.3906 | 1.4433 | 1400 | 0.2794 | 0.4290 | |
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| 0.3465 | 1.5464 | 1500 | 0.2807 | 0.4283 | |
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| 0.3564 | 1.6495 | 1600 | 0.2773 | 0.4238 | |
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| 0.3617 | 1.7526 | 1700 | 0.2750 | 0.4452 | |
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| 0.3808 | 1.8557 | 1800 | 0.2783 | 0.4229 | |
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| 0.3661 | 1.9588 | 1900 | 0.2761 | 0.4517 | |
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| 0.3952 | 2.0619 | 2000 | 0.2753 | 0.4201 | |
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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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