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update model card README.md
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README.md
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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: hubert-base-ls960-finetuned-gtzan-efficient-label-smoothed
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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-efficient-label-smoothed
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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 GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.2778
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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: 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: 30
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- label_smoothing_factor: 0.9
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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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| 2.2946 | 1.0 | 113 | 2.2960 | 0.42 |
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| 2.2821 | 2.0 | 226 | 2.2858 | 0.63 |
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| 2.2842 | 3.0 | 339 | 2.2848 | 0.68 |
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| 2.2685 | 4.0 | 452 | 2.2836 | 0.71 |
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| 2.2688 | 5.0 | 565 | 2.2838 | 0.71 |
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| 2.2901 | 6.0 | 678 | 2.2804 | 0.75 |
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| 2.2683 | 7.0 | 791 | 2.2831 | 0.7 |
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| 2.2695 | 8.0 | 904 | 2.2833 | 0.75 |
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| 2.268 | 9.0 | 1017 | 2.2793 | 0.8 |
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| 2.2836 | 10.0 | 1130 | 2.2867 | 0.68 |
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| 2.2704 | 11.0 | 1243 | 2.2811 | 0.78 |
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| 2.2665 | 12.0 | 1356 | 2.2783 | 0.83 |
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| 2.2663 | 13.0 | 1469 | 2.2782 | 0.85 |
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| 2.2669 | 14.0 | 1582 | 2.2759 | 0.88 |
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| 2.266 | 15.0 | 1695 | 2.2800 | 0.82 |
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| 2.266 | 16.0 | 1808 | 2.2797 | 0.82 |
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| 2.266 | 17.0 | 1921 | 2.2778 | 0.84 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.1.0.dev20230627+cu121
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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