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wilson-wei
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distilhubert-finetuned-gtzan

Audio Classification
Transformers
PyTorch
hubert
Generated from Trainer
Eval Results
Inference Endpoints
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update model card README.md

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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: 0.84
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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: 0.8605
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- - Accuracy: 0.84
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  ## Model description
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@@ -59,32 +59,27 @@ 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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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 2.1622 | 1.0 | 113 | 2.0289 | 0.36 |
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- | 1.6015 | 2.0 | 226 | 1.4290 | 0.59 |
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- | 1.1929 | 3.0 | 339 | 1.1003 | 0.7 |
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- | 0.9015 | 4.0 | 452 | 0.8761 | 0.76 |
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- | 0.7038 | 5.0 | 565 | 0.7516 | 0.76 |
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- | 0.3261 | 6.0 | 678 | 0.7753 | 0.77 |
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- | 0.5327 | 7.0 | 791 | 0.6131 | 0.79 |
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- | 0.1239 | 8.0 | 904 | 0.6283 | 0.8 |
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- | 0.1193 | 9.0 | 1017 | 0.5770 | 0.85 |
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- | 0.1405 | 10.0 | 1130 | 0.7979 | 0.8 |
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- | 0.0113 | 11.0 | 1243 | 0.7830 | 0.81 |
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- | 0.1392 | 12.0 | 1356 | 0.7350 | 0.85 |
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- | 0.0065 | 13.0 | 1469 | 0.7935 | 0.82 |
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- | 0.0049 | 14.0 | 1582 | 0.8323 | 0.84 |
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- | 0.0041 | 15.0 | 1695 | 0.7644 | 0.86 |
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- | 0.0034 | 16.0 | 1808 | 0.8438 | 0.85 |
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- | 0.0247 | 17.0 | 1921 | 0.7781 | 0.86 |
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- | 0.003 | 18.0 | 2034 | 0.8368 | 0.84 |
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- | 0.0028 | 19.0 | 2147 | 0.8477 | 0.84 |
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- | 0.0031 | 20.0 | 2260 | 0.8605 | 0.84 |
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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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+ - Accuracy: 0.86
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+ - Loss: 0.7644
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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: 10
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  ### Training results
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+ | Training Loss | Epoch | Step | Accuracy | Validation Loss |
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+ |:-------------:|:-----:|:----:|:--------:|:---------------:|
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+ | 2.1622 | 1.0 | 113 | 0.36 | 2.0289 |
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+ | 1.6015 | 2.0 | 226 | 0.59 | 1.4290 |
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+ | 1.1929 | 3.0 | 339 | 0.7 | 1.1003 |
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+ | 0.9015 | 4.0 | 452 | 0.76 | 0.8761 |
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+ | 0.7038 | 5.0 | 565 | 0.76 | 0.7516 |
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+ | 0.3261 | 6.0 | 678 | 0.77 | 0.7753 |
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+ | 0.5327 | 7.0 | 791 | 0.79 | 0.6131 |
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+ | 0.1239 | 8.0 | 904 | 0.8 | 0.6283 |
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+ | 0.1193 | 9.0 | 1017 | 0.85 | 0.5770 |
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+ | 0.1405 | 10.0 | 1130 | 0.8 | 0.7979 |
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+ | 0.0113 | 11.0 | 1243 | 0.81 | 0.7830 |
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+ | 0.1392 | 12.0 | 1356 | 0.85 | 0.7350 |
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+ | 0.0065 | 13.0 | 1469 | 0.82 | 0.7935 |
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+ | 0.0049 | 14.0 | 1582 | 0.84 | 0.8323 |
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+ | 0.0041 | 15.0 | 1695 | 0.86 | 0.7644 |
 
 
 
 
 
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  ### Framework versions