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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 |
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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 |
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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: 0.9570 |
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- Accuracy: 0.86 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 20 |
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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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| 2.1586 | 1.0 | 112 | 2.0855 | 0.45 | |
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| 1.4771 | 2.0 | 225 | 1.3396 | 0.72 | |
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| 1.181 | 3.0 | 337 | 0.9735 | 0.76 | |
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| 0.8133 | 4.0 | 450 | 0.8692 | 0.76 | |
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| 0.5397 | 5.0 | 562 | 0.7118 | 0.81 | |
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| 0.3424 | 6.0 | 675 | 0.6237 | 0.81 | |
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| 0.2717 | 7.0 | 787 | 0.6551 | 0.83 | |
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| 0.2653 | 8.0 | 900 | 0.6707 | 0.83 | |
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| 0.0503 | 9.0 | 1012 | 0.7025 | 0.84 | |
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| 0.0168 | 10.0 | 1125 | 0.7643 | 0.87 | |
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| 0.1125 | 11.0 | 1237 | 0.8550 | 0.86 | |
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| 0.155 | 12.0 | 1350 | 0.9796 | 0.82 | |
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| 0.005 | 13.0 | 1462 | 0.9539 | 0.86 | |
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| 0.0038 | 14.0 | 1575 | 0.9206 | 0.86 | |
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| 0.0035 | 15.0 | 1687 | 0.8725 | 0.88 | |
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| 0.051 | 16.0 | 1800 | 0.9980 | 0.86 | |
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| 0.003 | 17.0 | 1912 | 0.9579 | 0.86 | |
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| 0.0025 | 18.0 | 2025 | 0.9735 | 0.86 | |
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| 0.0023 | 19.0 | 2137 | 0.9589 | 0.86 | |
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| 0.0022 | 19.91 | 2240 | 0.9570 | 0.86 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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