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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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- 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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- Transformers 4.32.0.dev0
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- Pytorch 2.0.1+
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.78
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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: 0.7136
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- Accuracy: 0.78
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 2.1794 | 1.0 | 112 | 2.1111 | 0.29 |
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| 1.8527 | 2.0 | 225 | 1.7586 | 0.33 |
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| 1.4409 | 3.0 | 337 | 1.4728 | 0.48 |
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| 1.4484 | 4.0 | 450 | 1.3092 | 0.59 |
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| 1.409 | 5.0 | 562 | 1.1073 | 0.68 |
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| 1.0274 | 6.0 | 675 | 1.1107 | 0.67 |
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| 1.0141 | 7.0 | 787 | 0.9898 | 0.7 |
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| 0.8946 | 8.0 | 900 | 0.9540 | 0.68 |
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| 1.0337 | 9.0 | 1012 | 0.8722 | 0.72 |
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| 0.8065 | 10.0 | 1125 | 0.8196 | 0.74 |
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| 1.0335 | 11.0 | 1237 | 0.7891 | 0.75 |
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| 0.7712 | 12.0 | 1350 | 0.7298 | 0.78 |
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| 0.7041 | 13.0 | 1462 | 0.7240 | 0.8 |
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| 0.7287 | 14.0 | 1575 | 0.7206 | 0.78 |
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| 0.9821 | 14.93 | 1680 | 0.7136 | 0.78 |
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### Framework versions
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- Transformers 4.32.0.dev0
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- Pytorch 2.0.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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