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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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- genbed |
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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-nyagen-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-nyagen-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 GENBED - BEM dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1727 |
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- Wer: 0.2465 |
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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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| 6.9978 | 0.1364 | 100 | 0.6384 | 0.5015 | |
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| 0.482 | 0.2729 | 200 | 0.2777 | 0.3713 | |
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| 0.3907 | 0.4093 | 300 | 0.2484 | 0.3481 | |
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| 0.3782 | 0.5457 | 400 | 0.2290 | 0.3232 | |
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| 0.3316 | 0.6821 | 500 | 0.2222 | 0.3148 | |
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| 0.3158 | 0.8186 | 600 | 0.2127 | 0.3042 | |
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| 0.3199 | 0.9550 | 700 | 0.2106 | 0.2932 | |
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| 0.3223 | 1.0914 | 800 | 0.2013 | 0.2826 | |
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| 0.3075 | 1.2278 | 900 | 0.1975 | 0.2709 | |
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| 0.3015 | 1.3643 | 1000 | 0.1942 | 0.2762 | |
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| 0.3049 | 1.5007 | 1100 | 0.1895 | 0.2729 | |
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| 0.3029 | 1.6371 | 1200 | 0.1888 | 0.2718 | |
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| 0.2626 | 1.7735 | 1300 | 0.1866 | 0.2683 | |
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| 0.2803 | 1.9100 | 1400 | 0.1830 | 0.2615 | |
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| 0.2725 | 2.0464 | 1500 | 0.1814 | 0.2626 | |
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| 0.2732 | 2.1828 | 1600 | 0.1783 | 0.2641 | |
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| 0.249 | 2.3192 | 1700 | 0.1828 | 0.2560 | |
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| 0.2423 | 2.4557 | 1800 | 0.1762 | 0.2480 | |
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| 0.2668 | 2.5921 | 1900 | 0.1732 | 0.2458 | |
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| 0.2653 | 2.7285 | 2000 | 0.1727 | 0.2460 | |
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| 0.2614 | 2.8649 | 2100 | 0.1749 | 0.2533 | |
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| 0.2474 | 3.0014 | 2200 | 0.1733 | 0.2438 | |
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| 0.2317 | 3.1378 | 2300 | 0.1767 | 0.2447 | |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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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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