End of training
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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:
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- Accuracy: 0.
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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:
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size:
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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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| 0.0016 | 11.0 | 2475 | 0.8999 | 0.85 |
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| 0.0013 | 12.0 | 2700 | 0.8947 | 0.86 |
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| 0.0015 | 13.0 | 2925 | 0.9257 | 0.85 |
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| 0.0009 | 14.0 | 3150 | 1.0211 | 0.82 |
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| 0.0009 | 15.0 | 3375 | 0.9288 | 0.84 |
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| 0.0008 | 16.0 | 3600 | 0.9672 | 0.82 |
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| 0.0009 | 17.0 | 3825 | 1.0717 | 0.82 |
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| 0.0756 | 18.0 | 4050 | 1.0646 | 0.82 |
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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: 0.78
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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: 0.7054
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- Accuracy: 0.78
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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: 6e-05
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- train_batch_size: 6
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- eval_batch_size: 6
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 12
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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: 10
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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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| 2.0862 | 0.99 | 79 | 1.8937 | 0.42 |
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| 1.4131 | 2.0 | 159 | 1.3534 | 0.64 |
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| 1.0176 | 2.99 | 238 | 1.0980 | 0.66 |
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| 0.6508 | 4.0 | 318 | 0.7554 | 0.86 |
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| 0.5523 | 4.99 | 397 | 0.7662 | 0.76 |
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| 0.398 | 6.0 | 477 | 0.6944 | 0.8 |
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| 0.2008 | 6.99 | 556 | 0.6739 | 0.76 |
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| 0.1801 | 8.0 | 636 | 0.7623 | 0.78 |
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| 0.1044 | 8.99 | 715 | 0.7073 | 0.8 |
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| 0.0788 | 9.94 | 790 | 0.7054 | 0.78 |
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### Framework versions
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pytorch_model.bin
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size 94783376
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