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nacielo
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wav2GPT2MusiNewStricD3E5

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
speech-encoder-decoder
Generated from Trainer
Inference Endpoints
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update model card README.md

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@@ -16,12 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.2775
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- - Rouge1: 37.5957
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- - Rouge2: 10.8859
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- - Rougel: 29.7559
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- - Rougelsum: 29.7904
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- - Gen Len: 33.19
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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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- | 3.1175 | 1.0 | 983 | 2.5054 | 36.6389 | 9.7932 | 28.7186 | 28.771 | 30.04 |
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- | 2.6547 | 2.0 | 1966 | 2.3880 | 36.5342 | 10.597 | 29.092 | 29.0762 | 28.1 |
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- | 2.5787 | 3.0 | 2949 | 2.3239 | 37.5926 | 10.5376 | 29.0149 | 29.0558 | 34.72 |
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- | 2.5014 | 4.0 | 3932 | 2.2907 | 36.1982 | 9.8055 | 29.3162 | 29.3555 | 33.97 |
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- | 2.4805 | 5.0 | 4915 | 2.2775 | 37.5957 | 10.8859 | 29.7559 | 29.7904 | 33.19 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.5120
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+ - Rouge1: 20.9558
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+ - Rouge2: 3.2839
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+ - Rougel: 19.7122
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+ - Rougelsum: 19.6901
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+ - Gen Len: 67.79
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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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+ | 2.7207 | 1.0 | 959 | 2.7234 | 20.368 | 2.6174 | 18.7438 | 18.7592 | 63.11 |
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+ | 2.4751 | 2.0 | 1918 | 2.6164 | 20.9097 | 3.3813 | 19.3157 | 19.386 | 66.29 |
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+ | 2.3977 | 3.0 | 2877 | 2.5586 | 21.178 | 3.5221 | 19.9418 | 19.9061 | 67.82 |
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+ | 2.3305 | 4.0 | 3836 | 2.5236 | 21.4817 | 3.5503 | 20.3017 | 20.2749 | 67.58 |
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+ | 2.3079 | 5.0 | 4795 | 2.5120 | 20.9558 | 3.2839 | 19.7122 | 19.6901 | 67.79 |
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  ### Framework versions