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update model card README.md
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README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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.
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- Accuracy: 0.
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## Model description
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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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:
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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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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.85
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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
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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: 0.6094
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- Accuracy: 0.85
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## Model description
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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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: 16
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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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| 2.1935 | 0.99 | 56 | 2.1282 | 0.42 |
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| 1.6089 | 2.0 | 113 | 1.5367 | 0.57 |
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| 1.2446 | 2.99 | 169 | 1.1485 | 0.74 |
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| 0.98 | 4.0 | 226 | 0.9621 | 0.76 |
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| 0.7296 | 4.99 | 282 | 0.7948 | 0.82 |
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| 0.5111 | 6.0 | 339 | 0.7578 | 0.79 |
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| 0.583 | 6.99 | 395 | 0.6152 | 0.86 |
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| 0.4002 | 8.0 | 452 | 0.5863 | 0.85 |
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| 0.2924 | 8.99 | 508 | 0.5834 | 0.84 |
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| 0.1789 | 10.0 | 565 | 0.6087 | 0.85 |
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| 0.1181 | 10.99 | 621 | 0.5911 | 0.84 |
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| 0.0673 | 12.0 | 678 | 0.5887 | 0.85 |
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| 0.0633 | 12.99 | 734 | 0.6294 | 0.84 |
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| 0.0393 | 14.0 | 791 | 0.6205 | 0.84 |
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| 0.0362 | 14.99 | 847 | 0.6382 | 0.85 |
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| 0.0328 | 15.86 | 896 | 0.6094 | 0.85 |
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### Framework versions
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