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End of training

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  1. README.md +24 -19
  2. pytorch_model.bin +1 -1
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: 0.8
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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: 1.0712
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- - Accuracy: 0.8
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  ## Model description
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@@ -52,34 +52,39 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0008
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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: 0.2
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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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- | 0.8762 | 1.0 | 57 | 1.6973 | 0.53 |
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- | 1.575 | 2.0 | 114 | 1.7040 | 0.47 |
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- | 1.5454 | 3.0 | 171 | 1.6838 | 0.55 |
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- | 1.4241 | 4.0 | 228 | 1.3264 | 0.61 |
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- | 0.8853 | 5.0 | 285 | 1.1286 | 0.66 |
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- | 0.8654 | 6.0 | 342 | 1.0538 | 0.67 |
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- | 0.5314 | 7.0 | 399 | 1.0161 | 0.7 |
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- | 0.4237 | 8.0 | 456 | 1.0739 | 0.74 |
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- | 0.1364 | 9.0 | 513 | 1.2816 | 0.72 |
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- | 0.0263 | 10.0 | 570 | 1.0712 | 0.8 |
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.34.0.dev0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.5
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  - Tokenizers 0.14.0
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9
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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: 0.6062
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+ - Accuracy: 0.9
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  ## Model description
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  ### Training hyperparameters
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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: 8
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+ - eval_batch_size: 8
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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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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.0776 | 1.0 | 113 | 1.9082 | 0.48 |
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+ | 1.3768 | 2.0 | 226 | 1.3052 | 0.63 |
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+ | 1.0741 | 3.0 | 339 | 0.9721 | 0.79 |
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+ | 0.778 | 4.0 | 452 | 0.8452 | 0.76 |
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+ | 0.6383 | 5.0 | 565 | 0.5935 | 0.85 |
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+ | 0.3313 | 6.0 | 678 | 0.5947 | 0.81 |
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+ | 0.3514 | 7.0 | 791 | 0.6064 | 0.8 |
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+ | 0.0922 | 8.0 | 904 | 0.5759 | 0.81 |
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+ | 0.1757 | 9.0 | 1017 | 0.4683 | 0.88 |
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+ | 0.0496 | 10.0 | 1130 | 0.5958 | 0.86 |
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+ | 0.0141 | 11.0 | 1243 | 0.5512 | 0.87 |
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+ | 0.0345 | 12.0 | 1356 | 0.6297 | 0.86 |
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+ | 0.0079 | 13.0 | 1469 | 0.6009 | 0.89 |
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+ | 0.0072 | 14.0 | 1582 | 0.6069 | 0.9 |
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+ | 0.007 | 15.0 | 1695 | 0.6062 | 0.9 |
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  ### Framework versions
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+ - Transformers 4.35.0.dev0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.5
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  - Tokenizers 0.14.0
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