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README.md
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@@ -18,8 +18,8 @@ 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.
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- Accuracy: 0.
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## Model description
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-05
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- lr_scheduler_type:
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs:
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- label_smoothing_factor: 0.05
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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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| 0.3455 | 9.0 | 1017 | 0.7507 | 0.87 |
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| 0.2924 | 10.0 | 1130 | 0.8073 | 0.86 |
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| 0.2925 | 11.0 | 1243 | 0.7269 | 0.86 |
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| 0.2853 | 12.0 | 1356 | 0.7186 | 0.86 |
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### Framework versions
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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: 0.7162
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- Accuracy: 0.88
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## Model description
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-05
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 8
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- label_smoothing_factor: 0.05
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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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| 1.5923 | 1.0 | 113 | 1.7310 | 0.44 |
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| 1.2071 | 2.0 | 226 | 1.2546 | 0.62 |
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| 1.0673 | 3.0 | 339 | 0.9320 | 0.76 |
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| 0.8149 | 4.0 | 452 | 0.8768 | 0.81 |
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| 0.4999 | 5.0 | 565 | 0.7154 | 0.86 |
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| 0.3562 | 6.0 | 678 | 0.6631 | 0.89 |
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| 0.3852 | 7.0 | 791 | 0.7136 | 0.87 |
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| 0.4476 | 8.0 | 904 | 0.7162 | 0.88 |
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### Framework versions
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