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update model card README.md

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@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.5728
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- - Wer Ortho: 0.3943
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  - Wer: 0.3664
 
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  ## Model description
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@@ -64,28 +64,28 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
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- |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
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- | 0.7731 | 1.45 | 100 | 0.7280 | 0.3863 | 0.3740 |
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- | 0.2103 | 2.9 | 200 | 0.5116 | 0.3859 | 0.3661 |
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- | 0.0633 | 4.35 | 300 | 0.4967 | 0.3008 | 0.2810 |
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- | 0.0249 | 5.8 | 400 | 0.5003 | 0.3477 | 0.3299 |
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- | 0.0143 | 7.25 | 500 | 0.5191 | 0.3660 | 0.3510 |
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- | 0.0053 | 8.7 | 600 | 0.5149 | 0.3221 | 0.3070 |
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- | 0.0035 | 10.14 | 700 | 0.5345 | 0.3443 | 0.3266 |
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- | 0.0027 | 11.59 | 800 | 0.5339 | 0.3344 | 0.3175 |
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- | 0.0026 | 13.04 | 900 | 0.5435 | 0.3328 | 0.3134 |
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- | 0.0037 | 14.49 | 1000 | 0.5346 | 0.2714 | 0.2506 |
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- | 0.0045 | 15.94 | 1100 | 0.5438 | 0.3389 | 0.3220 |
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- | 0.0028 | 17.39 | 1200 | 0.5588 | 0.2740 | 0.2551 |
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- | 0.0036 | 18.84 | 1300 | 0.5466 | 0.2702 | 0.2728 |
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- | 0.0035 | 20.29 | 1400 | 0.5364 | 0.3332 | 0.3119 |
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- | 0.0056 | 21.74 | 1500 | 0.5608 | 0.2721 | 0.2506 |
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- | 0.0037 | 23.19 | 1600 | 0.5443 | 0.3027 | 0.2833 |
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- | 0.0035 | 24.64 | 1700 | 0.5466 | 0.3866 | 0.3631 |
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- | 0.0024 | 26.09 | 1800 | 0.5628 | 0.3416 | 0.3198 |
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- | 0.0036 | 27.54 | 1900 | 0.5495 | 0.3122 | 0.2946 |
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- | 0.0016 | 28.99 | 2000 | 0.5728 | 0.3943 | 0.3664 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.5728
 
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  - Wer: 0.3664
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+ - Wer Ortho: 0.3943
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|
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+ | 0.7731 | 1.45 | 100 | 0.7280 | 0.3740 | 0.3863 |
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+ | 0.2103 | 2.9 | 200 | 0.5116 | 0.3661 | 0.3859 |
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+ | 0.0633 | 4.35 | 300 | 0.4967 | 0.2810 | 0.3008 |
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+ | 0.0249 | 5.8 | 400 | 0.5003 | 0.3299 | 0.3477 |
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+ | 0.0143 | 7.25 | 500 | 0.5191 | 0.3510 | 0.3660 |
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+ | 0.0053 | 8.7 | 600 | 0.5149 | 0.3070 | 0.3221 |
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+ | 0.0035 | 10.14 | 700 | 0.5345 | 0.3266 | 0.3443 |
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+ | 0.0027 | 11.59 | 800 | 0.5339 | 0.3175 | 0.3344 |
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+ | 0.0026 | 13.04 | 900 | 0.5435 | 0.3134 | 0.3328 |
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+ | 0.0037 | 14.49 | 1000 | 0.5346 | 0.2506 | 0.2714 |
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+ | 0.0045 | 15.94 | 1100 | 0.5438 | 0.3220 | 0.3389 |
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+ | 0.0028 | 17.39 | 1200 | 0.5588 | 0.2551 | 0.2740 |
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+ | 0.0036 | 18.84 | 1300 | 0.5466 | 0.2728 | 0.2702 |
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+ | 0.0035 | 20.29 | 1400 | 0.5364 | 0.3119 | 0.3332 |
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+ | 0.0056 | 21.74 | 1500 | 0.5608 | 0.2506 | 0.2721 |
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+ | 0.0037 | 23.19 | 1600 | 0.5443 | 0.2833 | 0.3027 |
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+ | 0.0035 | 24.64 | 1700 | 0.5466 | 0.3631 | 0.3866 |
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+ | 0.0024 | 26.09 | 1800 | 0.5628 | 0.3198 | 0.3416 |
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+ | 0.0036 | 27.54 | 1900 | 0.5495 | 0.2946 | 0.3122 |
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+ | 0.0016 | 28.99 | 2000 | 0.5728 | 0.3664 | 0.3943 |
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  ### Framework versions