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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-female-20hrs-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-female-20hrs-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: 0.5260 |
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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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| 13.9528 | 0.0752 | 100 | inf | 1.0431 | |
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| 6.1846 | 0.1505 | 200 | inf | 1.0030 | |
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| 5.4651 | 0.2257 | 300 | inf | 1.0386 | |
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| 4.4356 | 0.3010 | 400 | inf | 0.8831 | |
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| 2.2016 | 0.3762 | 500 | inf | 0.6218 | |
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| 1.8013 | 0.4515 | 600 | inf | 0.5746 | |
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| 1.7499 | 0.5267 | 700 | inf | 0.5793 | |
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| 1.6979 | 0.6020 | 800 | inf | 0.5501 | |
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| 1.5567 | 0.6772 | 900 | inf | 0.5439 | |
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| 1.6301 | 0.7524 | 1000 | inf | 0.5355 | |
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| 1.6362 | 0.8277 | 1100 | inf | 0.5367 | |
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| 1.5247 | 0.9029 | 1200 | inf | 0.5326 | |
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| 1.4012 | 0.9782 | 1300 | inf | 0.5346 | |
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| 1.6397 | 1.0534 | 1400 | inf | 0.5301 | |
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| 1.5258 | 1.1287 | 1500 | inf | 0.5285 | |
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| 1.4144 | 1.2039 | 1600 | inf | 0.5244 | |
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| 1.4363 | 1.2792 | 1700 | inf | 0.5144 | |
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| 1.3733 | 1.3544 | 1800 | inf | 0.5358 | |
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| 1.4592 | 1.4296 | 1900 | inf | 0.5598 | |
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| 1.3499 | 1.5049 | 2000 | inf | 0.5192 | |
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| 1.4039 | 1.5801 | 2100 | inf | 0.5228 | |
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| 1.4057 | 1.6554 | 2200 | inf | 0.5289 | |
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| 1.4961 | 1.7306 | 2300 | inf | 0.5323 | |
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| 1.3975 | 1.8059 | 2400 | inf | 0.5119 | |
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| 1.4725 | 1.8811 | 2500 | inf | 0.5260 | |
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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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