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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- marsyas/gtzan |
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metrics: |
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- accuracy |
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model-index: |
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- name: distilhubert-finetuned-gtzan-2 |
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results: [] |
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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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should probably proofread and complete it, then remove this comment. --> |
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# distilhubert-finetuned-gtzan-2 |
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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: 0.9149 |
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- Accuracy: 0.83 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 25 |
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- mixed_precision_training: Native AMP |
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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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| 2.0823 | 1.0 | 113 | 2.0903 | 0.46 | |
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| 1.5111 | 2.0 | 226 | 1.5342 | 0.6 | |
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| 1.2342 | 3.0 | 339 | 1.1036 | 0.68 | |
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| 0.8352 | 4.0 | 452 | 0.9137 | 0.78 | |
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| 0.5727 | 5.0 | 565 | 0.6258 | 0.81 | |
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| 0.3957 | 6.0 | 678 | 0.5984 | 0.83 | |
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| 0.1851 | 7.0 | 791 | 0.6269 | 0.82 | |
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| 0.1607 | 8.0 | 904 | 0.6945 | 0.79 | |
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| 0.1426 | 9.0 | 1017 | 0.6103 | 0.86 | |
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| 0.0519 | 10.0 | 1130 | 0.7502 | 0.81 | |
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| 0.0097 | 11.0 | 1243 | 0.7101 | 0.85 | |
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| 0.006 | 12.0 | 1356 | 0.8174 | 0.82 | |
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| 0.0039 | 13.0 | 1469 | 0.8008 | 0.84 | |
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| 0.0032 | 14.0 | 1582 | 0.8438 | 0.81 | |
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| 0.0027 | 15.0 | 1695 | 0.8206 | 0.82 | |
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| 0.0024 | 16.0 | 1808 | 0.8563 | 0.82 | |
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| 0.002 | 17.0 | 1921 | 0.8884 | 0.82 | |
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| 0.0018 | 18.0 | 2034 | 0.9148 | 0.82 | |
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| 0.0018 | 19.0 | 2147 | 0.9017 | 0.83 | |
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| 0.0016 | 20.0 | 2260 | 0.9178 | 0.83 | |
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| 0.0015 | 21.0 | 2373 | 0.9070 | 0.83 | |
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| 0.0014 | 22.0 | 2486 | 0.9033 | 0.83 | |
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| 0.0014 | 23.0 | 2599 | 0.8975 | 0.84 | |
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| 0.0013 | 24.0 | 2712 | 0.9160 | 0.83 | |
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| 0.0013 | 25.0 | 2825 | 0.9149 | 0.83 | |
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### Framework versions |
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- Transformers 4.29.0 |
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- Pytorch 2.0.1 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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