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update model card README.md

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  1. README.md +21 -16
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@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.86
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5011
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- - Accuracy: 0.86
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  ## Model description
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@@ -59,27 +59,32 @@ The following hyperparameters were used during training:
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 2.0054 | 1.0 | 113 | 1.8169 | 0.49 |
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- | 1.2593 | 2.0 | 226 | 1.1584 | 0.68 |
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- | 1.0159 | 3.0 | 339 | 0.9291 | 0.78 |
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- | 0.855 | 4.0 | 452 | 0.8475 | 0.73 |
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- | 0.5882 | 5.0 | 565 | 0.6780 | 0.76 |
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- | 0.3857 | 6.0 | 678 | 0.5296 | 0.85 |
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- | 0.3972 | 7.0 | 791 | 0.5024 | 0.86 |
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- | 0.14 | 8.0 | 904 | 0.5223 | 0.82 |
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- | 0.2591 | 9.0 | 1017 | 0.4893 | 0.85 |
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- | 0.141 | 10.0 | 1130 | 0.5011 | 0.86 |
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.32.0.dev0
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  - Pytorch 2.0.1+cu118
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- - Datasets 2.13.1
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  - Tokenizers 0.13.3
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.81
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9492
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+ - Accuracy: 0.81
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  ## Model description
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 15
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.1278 | 1.0 | 113 | 1.9945 | 0.46 |
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+ | 1.422 | 2.0 | 226 | 1.3210 | 0.63 |
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+ | 1.0769 | 3.0 | 339 | 0.9838 | 0.77 |
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+ | 0.8781 | 4.0 | 452 | 0.8076 | 0.75 |
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+ | 0.6584 | 5.0 | 565 | 0.6962 | 0.79 |
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+ | 0.4766 | 6.0 | 678 | 0.5555 | 0.84 |
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+ | 0.3916 | 7.0 | 791 | 0.5909 | 0.84 |
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+ | 0.1187 | 8.0 | 904 | 0.6129 | 0.81 |
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+ | 0.1442 | 9.0 | 1017 | 0.7126 | 0.79 |
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+ | 0.1238 | 10.0 | 1130 | 0.8089 | 0.8 |
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+ | 0.0291 | 11.0 | 1243 | 0.8908 | 0.79 |
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+ | 0.0821 | 12.0 | 1356 | 0.8962 | 0.81 |
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+ | 0.0104 | 13.0 | 1469 | 0.8957 | 0.81 |
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+ | 0.0311 | 14.0 | 1582 | 0.9264 | 0.81 |
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+ | 0.0107 | 15.0 | 1695 | 0.9492 | 0.81 |
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  ### Framework versions
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+ - Transformers 4.31.0
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  - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.4
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  - Tokenizers 0.13.3