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sfedar
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distilhubert-finetuned-gtzan

Audio Classification
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hubert
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1 Parent(s): 26cc6b9

End of training, 9 epochs, 4 batch size, writer batch size: 1000, 1 gradient accumulation steps, learning rate: 5e-05, 30 s

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Files changed (2) hide show
  1. README.md +13 -24
  2. model.safetensors +1 -1
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: 0.85
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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: 2.0298
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- - Accuracy: 0.85
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  ## Model description
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@@ -59,33 +59,22 @@ 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: 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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- | 2.1346 | 1.0 | 113 | 2.0688 | 0.43 |
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- | 1.4627 | 2.0 | 226 | 1.5207 | 0.54 |
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- | 1.1848 | 3.0 | 339 | 1.2524 | 0.61 |
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- | 0.7007 | 4.0 | 452 | 0.9106 | 0.7 |
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- | 0.5724 | 5.0 | 565 | 0.7507 | 0.81 |
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- | 0.3465 | 6.0 | 678 | 0.6838 | 0.83 |
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- | 0.2814 | 7.0 | 791 | 0.5810 | 0.84 |
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- | 0.0838 | 8.0 | 904 | 0.7549 | 0.79 |
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- | 0.0866 | 9.0 | 1017 | 0.6639 | 0.82 |
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- | 0.0118 | 10.0 | 1130 | 0.8318 | 0.83 |
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- | 0.0019 | 11.0 | 1243 | 0.8335 | 0.84 |
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- | 0.0004 | 12.0 | 1356 | 1.2910 | 0.83 |
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- | 0.0 | 13.0 | 1469 | 1.3991 | 0.85 |
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- | 0.0 | 14.0 | 1582 | 1.7816 | 0.8 |
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- | 0.0 | 15.0 | 1695 | 1.8906 | 0.82 |
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- | 0.0 | 16.0 | 1808 | 2.0635 | 0.83 |
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- | 0.0 | 17.0 | 1921 | 1.9376 | 0.85 |
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- | 0.0 | 18.0 | 2034 | 2.0849 | 0.83 |
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- | 0.0 | 19.0 | 2147 | 2.0363 | 0.85 |
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- | 0.0 | 20.0 | 2260 | 2.0298 | 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: 0.82
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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: 0.6050
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+ - Accuracy: 0.82
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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: 9
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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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+ | 1.9557 | 1.0 | 113 | 1.9166 | 0.41 |
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+ | 1.1928 | 2.0 | 226 | 1.2556 | 0.67 |
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+ | 1.0954 | 3.0 | 339 | 1.0473 | 0.72 |
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+ | 0.6237 | 4.0 | 452 | 0.8854 | 0.72 |
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+ | 0.4856 | 5.0 | 565 | 0.6624 | 0.84 |
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+ | 0.344 | 6.0 | 678 | 0.6091 | 0.82 |
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+ | 0.2819 | 7.0 | 791 | 0.6306 | 0.8 |
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+ | 0.1515 | 8.0 | 904 | 0.5855 | 0.82 |
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+ | 0.2444 | 9.0 | 1017 | 0.6050 | 0.82 |
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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