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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: 0.7031 |
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- Accuracy: 0.82 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 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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| 2.2612 | 1.0 | 57 | 2.2511 | 0.26 | |
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| 2.1275 | 2.0 | 114 | 2.0384 | 0.36 | |
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| 1.8071 | 3.0 | 171 | 1.7399 | 0.52 | |
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| 1.6381 | 4.0 | 228 | 1.5693 | 0.61 | |
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| 1.4188 | 5.0 | 285 | 1.3573 | 0.61 | |
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| 1.2974 | 6.0 | 342 | 1.2103 | 0.72 | |
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| 1.2146 | 7.0 | 399 | 1.1800 | 0.69 | |
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| 1.0725 | 8.0 | 456 | 1.0126 | 0.77 | |
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| 1.0492 | 9.0 | 513 | 0.9821 | 0.74 | |
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| 1.0529 | 10.0 | 570 | 0.9347 | 0.77 | |
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| 0.895 | 11.0 | 627 | 0.8520 | 0.79 | |
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| 0.7692 | 12.0 | 684 | 0.8451 | 0.8 | |
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| 0.6566 | 13.0 | 741 | 0.7763 | 0.82 | |
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| 0.5885 | 14.0 | 798 | 0.7852 | 0.8 | |
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| 0.619 | 15.0 | 855 | 0.7443 | 0.8 | |
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| 0.5572 | 16.0 | 912 | 0.7444 | 0.79 | |
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| 0.6493 | 17.0 | 969 | 0.7024 | 0.83 | |
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| 0.5499 | 18.0 | 1026 | 0.7137 | 0.81 | |
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| 0.5923 | 19.0 | 1083 | 0.7059 | 0.81 | |
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| 0.5556 | 20.0 | 1140 | 0.7031 | 0.82 | |
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### Framework versions |
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- Transformers 4.30.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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