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--- |
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license: apache-2.0 |
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base_model: facebook/hubert-base-ls960 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: hubert-base-ls960-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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# hubert-base-ls960-finetuned-gtzan |
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This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1107 |
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- Accuracy: 0.85 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:---------------:| |
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| 1.9975 | 1.0 | 225 | 0.47 | 1.8130 | |
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| 1.2415 | 2.0 | 450 | 0.57 | 1.3022 | |
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| 1.0225 | 3.0 | 675 | 0.645 | 1.1478 | |
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| 1.1012 | 4.0 | 900 | 0.755 | 0.8725 | |
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| 1.0753 | 5.0 | 1125 | 0.67 | 1.1645 | |
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| 0.5354 | 6.0 | 1350 | 0.66 | 1.3094 | |
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| 0.7805 | 7.0 | 1575 | 0.795 | 0.8406 | |
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| 0.3307 | 8.0 | 1800 | 0.795 | 0.9782 | |
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| 0.1861 | 9.0 | 2025 | 0.79 | 0.9140 | |
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| 0.2776 | 10.0 | 2250 | 0.795 | 1.1711 | |
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| 0.314 | 11.0 | 2475 | 0.825 | 0.9193 | |
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| 0.1785 | 12.0 | 2700 | 0.82 | 1.0272 | |
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| 0.1444 | 13.0 | 2925 | 0.845 | 0.9903 | |
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| 0.0122 | 14.0 | 3150 | 0.835 | 0.9974 | |
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| 0.0116 | 15.0 | 3375 | 0.85 | 0.9670 | |
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| 0.3403 | 31.0 | 3472 | 1.0085 | 0.85 | |
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| 0.3596 | 32.0 | 3585 | 1.3101 | 0.81 | |
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| 0.0242 | 33.0 | 3697 | 0.9612 | 0.86 | |
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| 0.1006 | 34.0 | 3810 | 1.1904 | 0.82 | |
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| 0.1034 | 35.0 | 3922 | 0.9582 | 0.86 | |
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| 0.195 | 36.0 | 4035 | 1.0223 | 0.84 | |
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| 0.0081 | 37.0 | 4147 | 1.2461 | 0.8 | |
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| 0.006 | 38.0 | 4260 | 0.9541 | 0.87 | |
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| 0.281 | 39.0 | 4372 | 0.9340 | 0.87 | |
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| 0.0491 | 40.0 | 4485 | 1.0942 | 0.85 | |
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| 0.0537 | 41.0 | 4597 | 1.1521 | 0.85 | |
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| 0.0017 | 42.0 | 4710 | 1.1738 | 0.85 | |
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| 0.0031 | 43.0 | 4822 | 1.1584 | 0.85 | |
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| 0.1107 | 44.0 | 4935 | 1.1503 | 0.86 | |
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| 0.0032 | 45.0 | 5047 | 1.0710 | 0.87 | |
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| 0.0027 | 46.0 | 5160 | 1.1310 | 0.86 | |
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| 0.0013 | 47.0 | 5272 | 1.1194 | 0.86 | |
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| 0.0023 | 48.0 | 5385 | 1.1173 | 0.85 | |
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| 0.0286 | 49.0 | 5497 | 1.1087 | 0.85 | |
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| 0.0133 | 49.91 | 5600 | 1.1107 | 0.85 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1 |
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- Datasets 2.15.0 |
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- Tokenizers 0.13.2 |
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