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distilhubert-finetuned-gtzan

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update model card README.md

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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: 0.85
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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 [Sandiago21/distilhubert-finetuned-gtzan](https://huggingface.co/Sandiago21/distilhubert-finetuned-gtzan) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9021
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- - Accuracy: 0.85
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  ## Model description
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@@ -59,27 +59,57 @@ 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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- | 0.2617 | 1.0 | 57 | 0.8101 | 0.76 |
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- | 0.3005 | 2.0 | 114 | 0.8589 | 0.82 |
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- | 0.0123 | 3.0 | 171 | 1.0596 | 0.8 |
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- | 0.0141 | 4.0 | 228 | 1.0238 | 0.81 |
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- | 0.0047 | 5.0 | 285 | 0.8953 | 0.83 |
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- | 0.0889 | 6.0 | 342 | 0.8765 | 0.86 |
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- | 0.0482 | 7.0 | 399 | 1.1115 | 0.83 |
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- | 0.0013 | 8.0 | 456 | 1.0884 | 0.84 |
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- | 0.0009 | 9.0 | 513 | 1.0055 | 0.85 |
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- | 0.0008 | 10.0 | 570 | 0.9021 | 0.85 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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 2.14.3
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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: 0.88
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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 [Sandiago21/distilhubert-finetuned-gtzan](https://huggingface.co/Sandiago21/distilhubert-finetuned-gtzan) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9951
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+ - Accuracy: 0.88
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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: 40
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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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+ | 0.0951 | 1.0 | 57 | 0.5566 | 0.87 |
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+ | 0.0629 | 2.0 | 114 | 0.6819 | 0.83 |
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+ | 0.0231 | 3.0 | 171 | 0.6118 | 0.86 |
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+ | 0.0159 | 4.0 | 228 | 0.9208 | 0.83 |
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+ | 0.0374 | 5.0 | 285 | 0.8746 | 0.85 |
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+ | 0.1714 | 6.0 | 342 | 0.6671 | 0.87 |
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+ | 0.2148 | 7.0 | 399 | 1.1850 | 0.79 |
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+ | 0.0147 | 8.0 | 456 | 1.0551 | 0.79 |
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+ | 0.0788 | 9.0 | 513 | 1.5179 | 0.79 |
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+ | 0.0015 | 10.0 | 570 | 1.3290 | 0.8 |
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+ | 0.0049 | 11.0 | 627 | 1.0943 | 0.85 |
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+ | 0.0012 | 12.0 | 684 | 1.0667 | 0.85 |
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+ | 0.0043 | 13.0 | 741 | 1.1816 | 0.82 |
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+ | 0.0015 | 14.0 | 798 | 0.9108 | 0.88 |
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+ | 0.0011 | 15.0 | 855 | 1.0289 | 0.87 |
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+ | 0.001 | 16.0 | 912 | 0.7696 | 0.87 |
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+ | 0.0006 | 17.0 | 969 | 0.8539 | 0.87 |
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+ | 0.1001 | 18.0 | 1026 | 1.1917 | 0.78 |
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+ | 0.0017 | 19.0 | 1083 | 1.0016 | 0.83 |
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+ | 0.0525 | 20.0 | 1140 | 0.9513 | 0.88 |
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+ | 0.0004 | 21.0 | 1197 | 0.9268 | 0.86 |
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+ | 0.0003 | 22.0 | 1254 | 1.1209 | 0.82 |
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+ | 0.0003 | 23.0 | 1311 | 0.9270 | 0.87 |
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+ | 0.0003 | 24.0 | 1368 | 1.1148 | 0.84 |
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+ | 0.0003 | 25.0 | 1425 | 1.0507 | 0.85 |
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+ | 0.0002 | 26.0 | 1482 | 1.0156 | 0.86 |
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+ | 0.0002 | 27.0 | 1539 | 1.0062 | 0.87 |
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+ | 0.0002 | 28.0 | 1596 | 1.0124 | 0.87 |
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+ | 0.0002 | 29.0 | 1653 | 1.0154 | 0.87 |
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+ | 0.0002 | 30.0 | 1710 | 1.0092 | 0.88 |
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+ | 0.0002 | 31.0 | 1767 | 1.0123 | 0.88 |
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+ | 0.0175 | 32.0 | 1824 | 0.9928 | 0.88 |
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+ | 0.0002 | 33.0 | 1881 | 1.0014 | 0.88 |
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+ | 0.0115 | 34.0 | 1938 | 0.9989 | 0.88 |
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+ | 0.0001 | 35.0 | 1995 | 0.9871 | 0.88 |
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+ | 0.0001 | 36.0 | 2052 | 0.9920 | 0.88 |
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+ | 0.0002 | 37.0 | 2109 | 0.9974 | 0.88 |
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+ | 0.0002 | 38.0 | 2166 | 0.9950 | 0.88 |
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+ | 0.0001 | 39.0 | 2223 | 0.9997 | 0.88 |
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+ | 0.0001 | 40.0 | 2280 | 0.9951 | 0.88 |
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  ### Framework versions
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  - Transformers 4.31.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.13.1
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  - Tokenizers 0.13.3