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update model card README.md

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@@ -17,12 +17,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7159
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- - Rouge1: 51.0246
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- - Rouge2: 28.8904
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- - Rougel: 41.9694
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- - Rougelsum: 41.9864
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- - Gen Len: 57.62
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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- | 2.3604 | 1.0 | 1361 | 1.8562 | 29.3488 | 8.9477 | 21.7546 | 21.8458 | 49.94 |
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- | 1.8249 | 2.0 | 2722 | 1.4736 | 35.8525 | 12.9644 | 26.8468 | 26.8883 | 53.59 |
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- | 1.4928 | 3.0 | 4083 | 1.1557 | 36.0664 | 11.6796 | 26.6999 | 26.7209 | 65.05 |
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- | 1.149 | 4.0 | 5444 | 0.8567 | 45.1488 | 21.9847 | 35.4935 | 35.6169 | 56.51 |
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- | 0.862 | 5.0 | 6805 | 0.7159 | 51.0246 | 28.8904 | 41.9694 | 41.9864 | 57.62 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4596
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+ - Rouge1: 67.0305
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+ - Rouge2: 49.4145
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+ - Rougel: 59.4632
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+ - Rougelsum: 59.5132
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+ - Gen Len: 47.98
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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+ | 2.5281 | 1.0 | 983 | 1.7656 | 47.2738 | 19.609 | 35.166 | 35.1418 | 39.81 |
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+ | 1.8844 | 2.0 | 1966 | 1.4416 | 48.4369 | 22.034 | 36.3312 | 36.3541 | 41.88 |
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+ | 1.6071 | 3.0 | 2949 | 1.2060 | 49.7668 | 24.7504 | 38.8626 | 38.8523 | 37.8 |
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+ | 1.3867 | 4.0 | 3932 | 1.0056 | 52.8821 | 28.115 | 40.5389 | 40.5263 | 44.19 |
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+ | 1.1964 | 5.0 | 4915 | 0.8299 | 56.3235 | 32.1936 | 44.4629 | 44.3334 | 44.24 |
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+ | 1.0301 | 6.0 | 5898 | 0.6930 | 59.6505 | 36.3548 | 48.4558 | 48.3634 | 44.14 |
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+ | 0.904 | 7.0 | 6881 | 0.5916 | 61.3377 | 40.3586 | 50.8339 | 50.7188 | 46.15 |
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+ | 0.7985 | 8.0 | 7864 | 0.5157 | 64.7817 | 45.3792 | 56.0262 | 55.9178 | 47.7 |
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+ | 0.7125 | 9.0 | 8847 | 0.4722 | 66.0546 | 47.0456 | 57.422 | 57.37 | 48.35 |
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+ | 0.6514 | 10.0 | 9830 | 0.4596 | 67.0305 | 49.4145 | 59.4632 | 59.5132 | 47.98 |
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  ### Framework versions