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jamesthong
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distilhubert-finetuned-gtzan

Audio Classification
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hubert
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update model card README.md

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  1. README.md +23 -23
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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 [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: 0.8389
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- - Accuracy: 0.85
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  ## Model description
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@@ -65,26 +65,26 @@ 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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- | 2.2212 | 1.0 | 113 | 2.1403 | 0.33 |
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- | 1.7338 | 2.0 | 226 | 1.7175 | 0.38 |
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- | 1.6091 | 3.0 | 339 | 1.2717 | 0.63 |
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- | 1.486 | 4.0 | 452 | 1.1239 | 0.66 |
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- | 0.9635 | 5.0 | 565 | 0.8998 | 0.75 |
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- | 0.7295 | 6.0 | 678 | 0.7689 | 0.77 |
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- | 0.6776 | 7.0 | 791 | 0.5876 | 0.81 |
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- | 0.4629 | 8.0 | 904 | 0.5705 | 0.82 |
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- | 0.5087 | 9.0 | 1017 | 0.5388 | 0.83 |
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- | 0.2993 | 10.0 | 1130 | 0.6192 | 0.83 |
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- | 0.0446 | 11.0 | 1243 | 0.6592 | 0.81 |
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- | 0.1498 | 12.0 | 1356 | 0.7227 | 0.82 |
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- | 0.0139 | 13.0 | 1469 | 0.6565 | 0.83 |
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- | 0.1203 | 14.0 | 1582 | 0.8235 | 0.83 |
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- | 0.3866 | 15.0 | 1695 | 0.6868 | 0.84 |
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- | 0.2157 | 16.0 | 1808 | 0.8739 | 0.83 |
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- | 0.1954 | 17.0 | 1921 | 0.8418 | 0.84 |
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- | 0.0051 | 18.0 | 2034 | 0.8042 | 0.84 |
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- | 0.0777 | 19.0 | 2147 | 0.8573 | 0.84 |
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- | 0.2714 | 20.0 | 2260 | 0.8389 | 0.85 |
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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: 0.9203
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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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+ | 2.2556 | 1.0 | 113 | 2.1665 | 0.33 |
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+ | 1.9061 | 2.0 | 226 | 1.7036 | 0.57 |
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+ | 1.6449 | 3.0 | 339 | 1.3540 | 0.54 |
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+ | 1.4074 | 4.0 | 452 | 1.1028 | 0.68 |
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+ | 1.0121 | 5.0 | 565 | 0.9766 | 0.68 |
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+ | 0.7831 | 6.0 | 678 | 0.8285 | 0.75 |
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+ | 0.9829 | 7.0 | 791 | 0.7499 | 0.77 |
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+ | 0.604 | 8.0 | 904 | 0.7093 | 0.77 |
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+ | 0.6329 | 9.0 | 1017 | 0.7041 | 0.82 |
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+ | 0.4323 | 10.0 | 1130 | 0.7244 | 0.83 |
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+ | 0.1782 | 11.0 | 1243 | 0.7925 | 0.8 |
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+ | 0.2571 | 12.0 | 1356 | 0.7031 | 0.84 |
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+ | 0.1453 | 13.0 | 1469 | 0.7866 | 0.8 |
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+ | 0.5919 | 14.0 | 1582 | 0.8135 | 0.82 |
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+ | 0.307 | 15.0 | 1695 | 0.7489 | 0.85 |
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+ | 0.2163 | 16.0 | 1808 | 0.9134 | 0.82 |
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+ | 0.2081 | 17.0 | 1921 | 0.9109 | 0.85 |
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+ | 0.1025 | 18.0 | 2034 | 0.9215 | 0.84 |
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+ | 0.0415 | 19.0 | 2147 | 0.9542 | 0.84 |
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+ | 0.481 | 20.0 | 2260 | 0.9203 | 0.83 |
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  ### Framework versions