danielgh commited on
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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: 0.86
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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: 0.5720
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- - Accuracy: 0.86
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  ## Model description
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@@ -59,28 +59,38 @@ 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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  - 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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- | 1.8941 | 1.0 | 113 | 1.8243 | 0.56 |
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- | 1.1572 | 2.0 | 226 | 1.1978 | 0.7 |
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- | 1.035 | 3.0 | 339 | 0.9851 | 0.72 |
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- | 0.6312 | 4.0 | 452 | 0.8181 | 0.77 |
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- | 0.5429 | 5.0 | 565 | 0.6398 | 0.83 |
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- | 0.3732 | 6.0 | 678 | 0.5851 | 0.83 |
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- | 0.2133 | 7.0 | 791 | 0.5662 | 0.85 |
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- | 0.1017 | 8.0 | 904 | 0.6408 | 0.81 |
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- | 0.1394 | 9.0 | 1017 | 0.5693 | 0.85 |
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- | 0.0788 | 10.0 | 1130 | 0.5720 | 0.86 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.38.2
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- - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.83
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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: 0.9399
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+ - Accuracy: 0.83
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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: 20
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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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+ | 2.1679 | 1.0 | 113 | 2.0910 | 0.38 |
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+ | 1.4665 | 2.0 | 226 | 1.4798 | 0.53 |
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+ | 1.2128 | 3.0 | 339 | 1.1715 | 0.64 |
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+ | 0.7499 | 4.0 | 452 | 0.9591 | 0.68 |
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+ | 0.6869 | 5.0 | 565 | 0.8078 | 0.76 |
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+ | 0.3399 | 6.0 | 678 | 0.7513 | 0.81 |
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+ | 0.3071 | 7.0 | 791 | 0.6606 | 0.84 |
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+ | 0.0791 | 8.0 | 904 | 0.6416 | 0.84 |
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+ | 0.1047 | 9.0 | 1017 | 0.7613 | 0.82 |
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+ | 0.0784 | 10.0 | 1130 | 0.8558 | 0.82 |
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+ | 0.0097 | 11.0 | 1243 | 0.9087 | 0.82 |
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+ | 0.0071 | 12.0 | 1356 | 0.9155 | 0.83 |
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+ | 0.0052 | 13.0 | 1469 | 0.9210 | 0.85 |
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+ | 0.0044 | 14.0 | 1582 | 0.9543 | 0.84 |
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+ | 0.0035 | 15.0 | 1695 | 0.9726 | 0.85 |
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+ | 0.0032 | 16.0 | 1808 | 0.9183 | 0.84 |
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+ | 0.0029 | 17.0 | 1921 | 0.9181 | 0.83 |
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+ | 0.0027 | 18.0 | 2034 | 0.9575 | 0.84 |
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+ | 0.0027 | 19.0 | 2147 | 0.9427 | 0.83 |
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+ | 0.0026 | 20.0 | 2260 | 0.9399 | 0.83 |
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  ### Framework versions
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+ - Transformers 4.39.2
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+ - Pytorch 2.2.2+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
config.json CHANGED
@@ -90,7 +90,7 @@
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  "num_hidden_layers": 2,
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  "pad_token_id": 0,
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  "torch_dtype": "float32",
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- "transformers_version": "4.38.2",
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  "use_weighted_layer_sum": false,
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  "vocab_size": 32
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  }
 
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  "num_hidden_layers": 2,
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  "pad_token_id": 0,
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  "torch_dtype": "float32",
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+ "transformers_version": "4.39.2",
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  "use_weighted_layer_sum": false,
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  "vocab_size": 32
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  }
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