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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-v3
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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-v3
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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: 0.5752
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- Accuracy: 0.83
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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: 8
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- eval_batch_size: 8
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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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| 1.9108 | 1.0 | 113 | 1.9472 | 0.43 |
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| 1.3286 | 2.0 | 226 | 1.4173 | 0.65 |
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| 1.032 | 3.0 | 339 | 0.9815 | 0.67 |
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| 0.726 | 4.0 | 452 | 0.7403 | 0.79 |
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| 0.4621 | 5.0 | 565 | 0.6390 | 0.8 |
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| 0.3439 | 6.0 | 678 | 0.5248 | 0.85 |
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| 0.1592 | 7.0 | 791 | 0.4861 | 0.86 |
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| 0.1283 | 8.0 | 904 | 0.4995 | 0.87 |
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| 0.1191 | 9.0 | 1017 | 0.4804 | 0.87 |
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| 0.0236 | 10.0 | 1130 | 0.6737 | 0.8 |
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| 0.0146 | 11.0 | 1243 | 0.6211 | 0.81 |
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| 0.0105 | 12.0 | 1356 | 0.5806 | 0.86 |
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| 0.008 | 13.0 | 1469 | 0.5645 | 0.84 |
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| 0.0082 | 14.0 | 1582 | 0.6033 | 0.83 |
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| 0.0072 | 15.0 | 1695 | 0.5752 | 0.83 |
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### Framework versions
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- Transformers 4.30.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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