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sfedar
/
distilhubert-finetuned-gtzan

Audio Classification
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hubert
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sfedar commited on
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1 Parent(s): 814f7ca

End of training, 20 epochs, 100 batch size, 1000 writer batch size, 1 gradient accumulation steps, learning rate: 4e-05, 30 s

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Files changed (3) hide show
  1. README.md +24 -24
  2. model.safetensors +1 -1
  3. runs/Sep24_09-25-43_25f044a4c02e/events.out.tfevents.1727169993.25f044a4c02e.36.0 +2 -2
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: 0.85
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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
@@ -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: 1.9665
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- - Accuracy: 0.85
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  ## Model description
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@@ -53,7 +53,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0001
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -67,26 +67,26 @@ 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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- | 2.1366 | 1.0 | 57 | 2.0376 | 0.46 |
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- | 1.4386 | 2.0 | 114 | 1.3668 | 0.63 |
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- | 1.0033 | 3.0 | 171 | 0.9527 | 0.7 |
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- | 0.6843 | 4.0 | 228 | 0.8626 | 0.71 |
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- | 0.48 | 5.0 | 285 | 0.5658 | 0.83 |
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- | 0.2779 | 6.0 | 342 | 0.5189 | 0.86 |
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- | 0.2089 | 7.0 | 399 | 0.6737 | 0.78 |
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- | 0.0855 | 8.0 | 456 | 0.8386 | 0.75 |
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- | 0.0262 | 9.0 | 513 | 0.7713 | 0.84 |
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- | 0.0056 | 10.0 | 570 | 0.8664 | 0.82 |
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- | 0.0103 | 11.0 | 627 | 1.0195 | 0.84 |
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- | 0.0001 | 12.0 | 684 | 1.2668 | 0.84 |
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- | 0.0 | 13.0 | 741 | 1.7110 | 0.83 |
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- | 0.0 | 14.0 | 798 | 1.9586 | 0.84 |
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- | 0.0 | 15.0 | 855 | 1.8981 | 0.85 |
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- | 0.0 | 16.0 | 912 | 2.0259 | 0.84 |
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- | 0.0 | 17.0 | 969 | 1.7196 | 0.85 |
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- | 0.0284 | 18.0 | 1026 | 2.1840 | 0.85 |
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- | 0.0 | 19.0 | 1083 | 1.9820 | 0.85 |
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- | 0.0 | 20.0 | 1140 | 1.9665 | 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: 0.86
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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
 
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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: 0.5120
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+ - Accuracy: 0.86
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 4e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.2584 | 1.0 | 57 | 2.2062 | 0.35 |
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+ | 1.8611 | 2.0 | 114 | 1.7924 | 0.53 |
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+ | 1.4492 | 3.0 | 171 | 1.3901 | 0.65 |
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+ | 1.0971 | 4.0 | 228 | 1.1676 | 0.69 |
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+ | 0.9848 | 5.0 | 285 | 0.9750 | 0.74 |
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+ | 0.8434 | 6.0 | 342 | 0.8434 | 0.74 |
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+ | 0.7321 | 7.0 | 399 | 0.7555 | 0.83 |
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+ | 0.5364 | 8.0 | 456 | 0.6995 | 0.79 |
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+ | 0.4557 | 9.0 | 513 | 0.6118 | 0.84 |
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+ | 0.4166 | 10.0 | 570 | 0.5975 | 0.83 |
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+ | 0.2729 | 11.0 | 627 | 0.5576 | 0.83 |
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+ | 0.2491 | 12.0 | 684 | 0.5737 | 0.82 |
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+ | 0.2211 | 13.0 | 741 | 0.5129 | 0.84 |
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+ | 0.1243 | 14.0 | 798 | 0.5710 | 0.83 |
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+ | 0.0904 | 15.0 | 855 | 0.5087 | 0.86 |
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+ | 0.0773 | 16.0 | 912 | 0.5836 | 0.8 |
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+ | 0.0598 | 17.0 | 969 | 0.4871 | 0.83 |
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+ | 0.0551 | 18.0 | 1026 | 0.4865 | 0.84 |
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+ | 0.0467 | 19.0 | 1083 | 0.5043 | 0.84 |
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+ | 0.0364 | 20.0 | 1140 | 0.5120 | 0.86 |
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  ### Framework versions
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