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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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| 0.0033 | 16.0 | 1808 | 0.7015 | 0.84 |
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| 0.046 | 17.0 | 1921 | 0.6880 | 0.85 |
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| 0.0028 | 18.0 | 2034 | 0.6841 | 0.84 |
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| 0.0027 | 19.0 | 2147 | 0.6894 | 0.85 |
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| 0.0028 | 20.0 | 2260 | 0.7011 | 0.85 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.0
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- Datasets 2.
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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: 0.83
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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: 0.8933
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- Accuracy: 0.83
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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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| 2.1059 | 1.0 | 113 | 1.9709 | 0.39 |
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| 1.4561 | 2.0 | 226 | 1.2865 | 0.59 |
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| 1.03 | 3.0 | 339 | 0.9918 | 0.75 |
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| 0.8979 | 4.0 | 452 | 0.8700 | 0.77 |
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| 0.6697 | 5.0 | 565 | 0.7090 | 0.79 |
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| 0.3289 | 6.0 | 678 | 0.6646 | 0.77 |
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| 0.3612 | 7.0 | 791 | 0.6384 | 0.83 |
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| 0.068 | 8.0 | 904 | 0.5989 | 0.85 |
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| 0.1159 | 9.0 | 1017 | 0.7136 | 0.83 |
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| 0.0228 | 10.0 | 1130 | 0.8329 | 0.84 |
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| 0.0484 | 11.0 | 1243 | 0.8401 | 0.84 |
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| 0.0283 | 12.0 | 1356 | 0.8522 | 0.84 |
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| 0.008 | 13.0 | 1469 | 0.8865 | 0.84 |
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| 0.0066 | 14.0 | 1582 | 0.9048 | 0.85 |
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| 0.0067 | 15.0 | 1695 | 0.8933 | 0.83 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.0
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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