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End of training

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README.md CHANGED
@@ -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: 0.82
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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: 1.3274
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- - Accuracy: 0.82
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  ## Model description
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@@ -53,29 +53,34 @@ More information needed
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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: 1
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- - eval_batch_size: 1
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 10
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  - mixed_precision_training: Native AMP
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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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- | 1.3436 | 1.0 | 899 | 1.3559 | 0.57 |
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- | 1.1232 | 2.0 | 1798 | 1.3862 | 0.65 |
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- | 0.0315 | 3.0 | 2697 | 0.8953 | 0.76 |
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- | 0.0174 | 4.0 | 3596 | 0.9777 | 0.81 |
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- | 0.9155 | 5.0 | 4495 | 1.0478 | 0.81 |
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- | 0.4285 | 6.0 | 5394 | 1.6165 | 0.78 |
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- | 0.0003 | 7.0 | 6293 | 0.9844 | 0.86 |
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- | 0.0001 | 8.0 | 7192 | 1.3545 | 0.82 |
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- | 0.0001 | 9.0 | 8091 | 1.3581 | 0.82 |
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- | 0.0001 | 10.0 | 8990 | 1.3274 | 0.82 |
 
 
 
 
 
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  ### Framework versions
 
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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
 
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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: 0.5678
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+ - Accuracy: 0.86
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  ## Model description
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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: 16
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+ - eval_batch_size: 16
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 15
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  - mixed_precision_training: Native AMP
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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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+ | 2.2153 | 1.0 | 57 | 2.1306 | 0.37 |
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+ | 1.5998 | 2.0 | 114 | 1.5355 | 0.59 |
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+ | 1.2268 | 3.0 | 171 | 1.1801 | 0.7 |
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+ | 0.8839 | 4.0 | 228 | 1.0267 | 0.68 |
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+ | 0.8058 | 5.0 | 285 | 0.8348 | 0.77 |
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+ | 0.6722 | 6.0 | 342 | 0.7497 | 0.78 |
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+ | 0.6603 | 7.0 | 399 | 0.6921 | 0.78 |
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+ | 0.4026 | 8.0 | 456 | 0.6814 | 0.8 |
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+ | 0.3244 | 9.0 | 513 | 0.6138 | 0.81 |
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+ | 0.2639 | 10.0 | 570 | 0.5887 | 0.85 |
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+ | 0.1619 | 11.0 | 627 | 0.6005 | 0.83 |
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+ | 0.1652 | 12.0 | 684 | 0.5589 | 0.83 |
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+ | 0.1354 | 13.0 | 741 | 0.6157 | 0.8 |
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+ | 0.0821 | 14.0 | 798 | 0.6221 | 0.83 |
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+ | 0.1009 | 15.0 | 855 | 0.5678 | 0.86 |
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  ### Framework versions
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