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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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- bigcgen |
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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-bigcgen-combined-30hrs-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-combined-30hrs-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 BIGCGEN - BEM dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: inf |
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- Wer: 0.5077 |
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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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- training_steps: 2500 |
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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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| 14.5866 | 0.0509 | 100 | inf | 1.0167 | |
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| 6.2466 | 0.1018 | 200 | inf | 1.0019 | |
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| 5.4142 | 0.1526 | 300 | inf | 0.9912 | |
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| 2.1374 | 0.2035 | 400 | inf | 0.5952 | |
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| 1.741 | 0.2544 | 500 | inf | 0.5641 | |
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| 1.6543 | 0.3053 | 600 | inf | 0.5607 | |
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| 1.6579 | 0.3561 | 700 | inf | 0.5585 | |
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| 1.676 | 0.4070 | 800 | inf | 0.5475 | |
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| 1.5245 | 0.4579 | 900 | inf | 0.5410 | |
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| 1.6324 | 0.5088 | 1000 | inf | 0.5278 | |
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| 1.6878 | 0.5597 | 1100 | inf | 0.5244 | |
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| 1.4994 | 0.6105 | 1200 | inf | 0.5259 | |
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| 1.544 | 0.6614 | 1300 | inf | 0.5211 | |
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| 1.5796 | 0.7123 | 1400 | inf | 0.5244 | |
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| 1.3625 | 0.7632 | 1500 | inf | 0.5235 | |
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| 1.4826 | 0.8140 | 1600 | inf | 0.5165 | |
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| 1.4439 | 0.8649 | 1700 | inf | 0.5227 | |
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| 1.4778 | 0.9158 | 1800 | inf | 0.5148 | |
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| 1.389 | 0.9667 | 1900 | inf | 0.5130 | |
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| 1.3863 | 1.0173 | 2000 | inf | 0.5177 | |
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| 1.516 | 1.0682 | 2100 | inf | 0.5082 | |
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| 1.474 | 1.1191 | 2200 | inf | 0.5106 | |
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| 1.465 | 1.1699 | 2300 | inf | 0.5077 | |
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| 1.484 | 1.2208 | 2400 | inf | 0.5090 | |
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| 1.3942 | 1.2717 | 2500 | inf | 0.5079 | |
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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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