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distilhubert-finetuned-gtzan

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  1. README.md +13 -13
  2. model.safetensors +1 -1
README.md CHANGED
@@ -23,7 +23,7 @@ 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
@@ -33,8 +33,8 @@ 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: 0.7382
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- - Accuracy: 0.8
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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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- | 1.8837 | 1.0 | 113 | 1.8422 | 0.49 |
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- | 1.1972 | 2.0 | 226 | 1.2628 | 0.66 |
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- | 1.0489 | 3.0 | 339 | 0.9828 | 0.76 |
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- | 0.6307 | 4.0 | 452 | 0.8398 | 0.74 |
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- | 0.6133 | 5.0 | 565 | 0.6901 | 0.77 |
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- | 0.3406 | 6.0 | 678 | 0.6487 | 0.81 |
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- | 0.283 | 7.0 | 791 | 0.6711 | 0.82 |
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- | 0.1263 | 8.0 | 904 | 0.7056 | 0.81 |
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- | 0.101 | 9.0 | 1017 | 0.6949 | 0.81 |
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- | 0.0862 | 10.0 | 1130 | 0.7382 | 0.8 |
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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: 0.83
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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: 0.5354
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+ - Accuracy: 0.83
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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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+ | 1.9725 | 1.0 | 113 | 1.8465 | 0.56 |
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+ | 1.1576 | 2.0 | 226 | 1.2083 | 0.68 |
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+ | 1.0421 | 3.0 | 339 | 0.8909 | 0.76 |
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+ | 0.7046 | 4.0 | 452 | 0.8047 | 0.76 |
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+ | 0.5828 | 5.0 | 565 | 0.6903 | 0.79 |
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+ | 0.3891 | 6.0 | 678 | 0.5487 | 0.83 |
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+ | 0.2439 | 7.0 | 791 | 0.5593 | 0.83 |
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+ | 0.122 | 8.0 | 904 | 0.5844 | 0.83 |
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+ | 0.1297 | 9.0 | 1017 | 0.5206 | 0.84 |
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+ | 0.0943 | 10.0 | 1130 | 0.5354 | 0.83 |
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  ### Framework versions
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