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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: 1.2425 |
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- Accuracy: 0.84 |
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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: 0.0005 |
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- train_batch_size: 8 |
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- eval_batch_size: 12 |
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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: 15 |
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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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| 1.2069 | 1.0 | 113 | 1.3361 | 0.5 | |
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| 1.5776 | 2.0 | 226 | 1.4992 | 0.43 | |
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| 1.2343 | 3.0 | 339 | 1.2779 | 0.48 | |
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| 0.8813 | 4.0 | 452 | 1.2418 | 0.62 | |
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| 0.8836 | 5.0 | 565 | 0.9679 | 0.71 | |
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| 0.7827 | 6.0 | 678 | 0.9275 | 0.7 | |
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| 0.4979 | 7.0 | 791 | 1.2511 | 0.69 | |
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| 0.466 | 8.0 | 904 | 1.0917 | 0.73 | |
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| 0.6358 | 9.0 | 1017 | 0.7578 | 0.81 | |
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| 0.5371 | 10.0 | 1130 | 1.2664 | 0.72 | |
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| 0.0353 | 11.0 | 1243 | 1.2281 | 0.77 | |
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| 0.0159 | 12.0 | 1356 | 1.5949 | 0.73 | |
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| 0.0011 | 13.0 | 1469 | 1.0783 | 0.85 | |
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| 0.0007 | 14.0 | 1582 | 1.3324 | 0.82 | |
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| 0.0007 | 15.0 | 1695 | 1.2425 | 0.84 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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