update model card README.md
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README.md
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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: 0.83
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.
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- train_batch_size: 4
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- eval_batch_size: 4
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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 |
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| 1.
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| 0.
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| 0.
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| 0.
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| 0.
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.
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- Datasets 2.1
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- Tokenizers 0.13.3
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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: 0.6925
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- Accuracy: 0.83
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001115511981046745
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- train_batch_size: 4
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- eval_batch_size: 4
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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: 9
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### Training results
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| Training Loss | Epoch | Step | Accuracy | Validation Loss |
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|:-------------:|:-----:|:----:|:--------:|:---------------:|
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| 1.278 | 1.0 | 112 | 0.57 | 1.3298 |
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| 0.8315 | 2.0 | 225 | 0.73 | 0.9432 |
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| 0.7709 | 3.0 | 337 | 0.72 | 0.9310 |
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| 0.5427 | 4.0 | 450 | 0.72 | 0.8738 |
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| 0.2645 | 4.98 | 560 | 0.79 | 0.6648 |
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| 0.245 | 6.0 | 672 | 0.83 | 0.6147 |
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| 0.1331 | 6.99 | 784 | 0.83 | 0.6305 |
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| 0.1863 | 8.0 | 896 | 0.6356 | 0.84 |
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| 0.0843 | 8.99 | 1008 | 0.6925 | 0.83 |
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### Framework versions
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- Transformers 4.30.2
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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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