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README.md CHANGED
@@ -3,9 +3,6 @@ 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
@@ -19,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # mms-1b-bigcgen-combined-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: 0.6353
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  ## Model description
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@@ -50,17 +47,38 @@ The following hyperparameters were used during training:
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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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- | 14.6532 | 0.0762 | 100 | inf | 1.0179 |
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- | 6.1697 | 0.1524 | 200 | inf | 1.0100 |
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- | 5.3981 | 0.2287 | 300 | inf | 1.0266 |
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- | 3.8668 | 0.3049 | 400 | inf | 0.6355 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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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  # mms-1b-bigcgen-combined-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 an unknown 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: 0.5167
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  ## Model description
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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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+ | 14.8448 | 0.0762 | 100 | inf | 1.0079 |
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+ | 6.2506 | 0.1524 | 200 | inf | 1.0042 |
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+ | 5.5314 | 0.2287 | 300 | inf | 1.0270 |
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+ | 3.4418 | 0.3049 | 400 | inf | 0.5906 |
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+ | 1.9396 | 0.3811 | 500 | inf | 0.5762 |
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+ | 1.698 | 0.4573 | 600 | inf | 0.5566 |
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+ | 1.5483 | 0.5335 | 700 | inf | 0.5571 |
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+ | 1.6501 | 0.6098 | 800 | inf | 0.5487 |
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+ | 1.5528 | 0.6860 | 900 | inf | 0.5471 |
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+ | 1.5398 | 0.7622 | 1000 | inf | 0.5479 |
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+ | 1.6413 | 0.8384 | 1100 | inf | 0.5304 |
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+ | 1.418 | 0.9146 | 1200 | inf | 0.5283 |
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+ | 1.5625 | 0.9909 | 1300 | inf | 0.5265 |
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+ | 1.4753 | 1.0671 | 1400 | inf | 0.5347 |
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+ | 1.616 | 1.1433 | 1500 | inf | 0.5309 |
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+ | 1.3802 | 1.2195 | 1600 | inf | 0.5246 |
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+ | 1.4105 | 1.2957 | 1700 | inf | 0.5197 |
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+ | 1.3793 | 1.3720 | 1800 | inf | 0.5288 |
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+ | 1.3991 | 1.4482 | 1900 | inf | 0.5140 |
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+ | 1.5838 | 1.5244 | 2000 | inf | 0.5239 |
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+ | 1.6283 | 1.6006 | 2100 | inf | 0.5144 |
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+ | 1.4131 | 1.6768 | 2200 | inf | 0.5135 |
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+ | 1.388 | 1.7530 | 2300 | inf | 0.5137 |
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+ | 1.3846 | 1.8293 | 2400 | inf | 0.5145 |
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+ | 1.497 | 1.9055 | 2500 | inf | 0.5167 |
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  ### Framework versions
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