Jonnhan commited on
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End of training

Browse files
README.md CHANGED
@@ -19,7 +19,7 @@ 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
@@ -29,8 +29,8 @@ 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: 1.1337
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- - Accuracy: 0.86
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  ## Model description
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@@ -62,16 +62,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.7102 | 1.0 | 899 | 0.9058 | 0.69 |
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- | 1.9987 | 2.0 | 1798 | 1.3215 | 0.71 |
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- | 0.0086 | 3.0 | 2697 | 0.9701 | 0.75 |
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- | 0.0284 | 4.0 | 3596 | 0.8695 | 0.82 |
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- | 0.1668 | 5.0 | 4495 | 1.1303 | 0.81 |
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- | 0.0013 | 6.0 | 5394 | 1.0664 | 0.84 |
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- | 0.0026 | 7.0 | 6293 | 1.0936 | 0.87 |
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- | 0.0003 | 8.0 | 7192 | 1.1882 | 0.86 |
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- | 0.0004 | 9.0 | 8091 | 1.2463 | 0.85 |
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- | 0.0002 | 10.0 | 8990 | 1.1337 | 0.86 |
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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: 0.87
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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: 1.0906
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+ - Accuracy: 0.87
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.8287 | 1.0 | 899 | 0.8991 | 0.68 |
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+ | 2.2164 | 2.0 | 1798 | 1.3184 | 0.71 |
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+ | 0.0099 | 3.0 | 2697 | 0.9288 | 0.78 |
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+ | 0.0679 | 4.0 | 3596 | 0.8131 | 0.84 |
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+ | 0.0119 | 5.0 | 4495 | 1.1122 | 0.8 |
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+ | 0.0051 | 6.0 | 5394 | 0.9594 | 0.86 |
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+ | 0.0008 | 7.0 | 6293 | 0.9475 | 0.87 |
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+ | 0.0002 | 8.0 | 7192 | 1.1026 | 0.86 |
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+ | 0.0002 | 9.0 | 8091 | 1.0751 | 0.87 |
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+ | 0.0002 | 10.0 | 8990 | 1.0906 | 0.87 |
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  ### Framework versions
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