End of training
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- pytorch_model.bin +1 -1
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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- training_steps:
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### Training results
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| 0.0161 | 20.35 | 2300 | 0.85 | 0.8464 |
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| 0.0157 | 21.24 | 2400 | 0.86 | 0.8459 |
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| 0.0039 | 22.12 | 2500 | 0.8 | 1.0282 |
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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: 0.83
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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: 0.9791
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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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- training_steps: 4000
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### Training results
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| 0.0161 | 20.35 | 2300 | 0.85 | 0.8464 |
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| 0.0157 | 21.24 | 2400 | 0.86 | 0.8459 |
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| 0.0039 | 22.12 | 2500 | 0.8 | 1.0282 |
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| 0.0157 | 23.01 | 2600 | 0.86 | 0.8649 |
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| 0.0119 | 23.89 | 2700 | 0.85 | 0.8894 |
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| 0.0129 | 24.78 | 2800 | 0.87 | 0.8624 |
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| 0.0124 | 25.66 | 2900 | 0.85 | 0.8862 |
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| 0.0025 | 26.55 | 3000 | 0.84 | 0.9097 |
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| 0.0197 | 27.43 | 3100 | 0.9150 | 0.85 |
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| 0.0193 | 28.32 | 3200 | 0.9986 | 0.83 |
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| 0.0119 | 29.2 | 3300 | 0.9001 | 0.87 |
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| 0.0017 | 30.09 | 3400 | 0.9599 | 0.83 |
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| 0.015 | 30.97 | 3500 | 0.9442 | 0.84 |
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| 0.0015 | 31.86 | 3600 | 0.9813 | 0.83 |
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| 0.0056 | 32.74 | 3700 | 0.9791 | 0.83 |
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### Framework versions
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pytorch_model.bin
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