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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: 0.8078 |
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- Accuracy: 0.81 |
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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: 12 |
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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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| 2.1001 | 1.0 | 75 | 2.0810 | 0.45 | |
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| 1.563 | 2.0 | 150 | 1.5605 | 0.59 | |
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| 1.1348 | 3.0 | 225 | 1.1216 | 0.73 | |
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| 0.8687 | 4.0 | 300 | 0.9611 | 0.75 | |
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| 0.6107 | 5.0 | 375 | 0.9266 | 0.71 | |
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| 0.55 | 6.0 | 450 | 0.7138 | 0.81 | |
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| 0.3267 | 7.0 | 525 | 0.7121 | 0.84 | |
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| 0.3366 | 8.0 | 600 | 0.7213 | 0.81 | |
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| 0.2463 | 9.0 | 675 | 0.7768 | 0.79 | |
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| 0.1388 | 10.0 | 750 | 0.8165 | 0.79 | |
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| 0.1413 | 11.0 | 825 | 0.7713 | 0.82 | |
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| 0.0578 | 12.0 | 900 | 0.7860 | 0.8 | |
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| 0.0329 | 13.0 | 975 | 0.7821 | 0.82 | |
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| 0.0287 | 14.0 | 1050 | 0.8172 | 0.82 | |
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| 0.0277 | 15.0 | 1125 | 0.8078 | 0.81 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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