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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-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2928
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- - Rouge1: 47.848
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- - Rouge2: 21.6764
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- - Rougel: 35.5314
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- - Rougelsum: 35.4639
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- - Gen Len: 40.82
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  ## Model description
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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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- | 2.8872 | 1.0 | 983 | 2.1971 | 37.1303 | 10.7391 | 30.2675 | 30.2912 | 38.88 |
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- | 2.3087 | 2.0 | 1966 | 1.9342 | 43.2573 | 16.4043 | 32.2734 | 32.2172 | 37.88 |
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- | 2.0355 | 3.0 | 2949 | 1.6786 | 42.6805 | 16.4311 | 31.9712 | 31.9628 | 32.77 |
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- | 1.7976 | 4.0 | 3932 | 1.4354 | 46.1514 | 20.0287 | 34.8065 | 34.7311 | 34.71 |
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- | 1.5571 | 5.0 | 4915 | 1.2928 | 47.848 | 21.6764 | 35.5314 | 35.4639 | 40.82 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.5623
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+ - Rouge1: 26.7441
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+ - Rouge2: 6.3706
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+ - Rougel: 23.6169
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+ - Rougelsum: 23.5887
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+ - Gen Len: 65.71
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  ## Model description
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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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+ | 3.187 | 1.0 | 959 | 2.8591 | 22.3571 | 4.0074 | 20.7932 | 20.8063 | 67.11 |
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+ | 2.4008 | 2.0 | 1918 | 2.3569 | 25.1707 | 4.7622 | 22.9043 | 22.934 | 59.9 |
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+ | 2.059 | 3.0 | 2877 | 1.9763 | 23.6382 | 4.0133 | 21.9178 | 21.9638 | 57.94 |
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+ | 1.7741 | 4.0 | 3836 | 1.6896 | 25.0574 | 5.335 | 22.7412 | 22.7141 | 64.13 |
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+ | 1.542 | 5.0 | 4795 | 1.5623 | 26.7441 | 6.3706 | 23.6169 | 23.5887 | 65.71 |
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  ### Framework versions