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timothy-geiger
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distilhubert-finetuned-gtzan

Audio Classification
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PyTorch
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hubert
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  1. README.md +19 -14
  2. model.safetensors +1 -1
  3. runs/Mar07_22-12-25_3009a6145419/events.out.tfevents.1709849546.3009a6145419.440.3 +2 -2
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: 0.84
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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: 1.0184
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- - Accuracy: 0.84
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  ## Model description
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@@ -59,23 +59,28 @@ 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: 10
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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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- | 1.6293 | 1.0 | 450 | 1.4785 | 0.51 |
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- | 1.4503 | 2.0 | 900 | 1.0904 | 0.68 |
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- | 0.1918 | 3.0 | 1350 | 0.6702 | 0.75 |
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- | 0.0857 | 4.0 | 1800 | 0.7173 | 0.79 |
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- | 0.0601 | 5.0 | 2250 | 0.9274 | 0.77 |
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- | 0.0047 | 6.0 | 2700 | 0.9787 | 0.81 |
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- | 0.6662 | 7.0 | 3150 | 1.0511 | 0.81 |
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- | 0.0012 | 8.0 | 3600 | 1.0870 | 0.84 |
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- | 0.0015 | 9.0 | 4050 | 0.9564 | 0.87 |
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- | 0.0012 | 10.0 | 4500 | 1.0184 | 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: 0.87
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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: 1.0924
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+ - Accuracy: 0.87
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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: 15
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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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+ | 1.7495 | 1.0 | 450 | 1.7168 | 0.52 |
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+ | 1.1633 | 2.0 | 900 | 1.0515 | 0.66 |
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+ | 0.3792 | 3.0 | 1350 | 0.7312 | 0.73 |
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+ | 0.5365 | 4.0 | 1800 | 0.9707 | 0.75 |
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+ | 0.0234 | 5.0 | 2250 | 1.1124 | 0.75 |
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+ | 0.0039 | 6.0 | 2700 | 0.9717 | 0.82 |
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+ | 0.1781 | 7.0 | 3150 | 1.0491 | 0.82 |
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+ | 0.0009 | 8.0 | 3600 | 1.1946 | 0.83 |
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+ | 0.0007 | 9.0 | 4050 | 1.1116 | 0.84 |
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+ | 0.0004 | 10.0 | 4500 | 1.0814 | 0.85 |
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+ | 0.0004 | 11.0 | 4950 | 1.1160 | 0.85 |
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+ | 0.0003 | 12.0 | 5400 | 1.1082 | 0.85 |
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+ | 0.0003 | 13.0 | 5850 | 1.1311 | 0.86 |
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+ | 0.0002 | 14.0 | 6300 | 1.1159 | 0.86 |
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+ | 0.0003 | 15.0 | 6750 | 1.0924 | 0.87 |
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  ### Framework versions
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