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update model card README.md
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README.md
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@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps:
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- total_train_batch_size:
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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### Framework versions
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This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: nan
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- Accuracy: 0.86
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 16
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 2.2625 | 1.0 | 56 | 2.2399 | 0.23 |
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| 1.7887 | 1.99 | 112 | 1.7278 | 0.4 |
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| 1.4728 | 2.99 | 168 | 1.4387 | 0.48 |
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| 1.1536 | 4.0 | 225 | 1.3178 | 0.54 |
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| 1.0758 | 5.0 | 281 | 1.1903 | 0.6 |
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| 0.9742 | 5.99 | 337 | 0.8416 | 0.72 |
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| 0.8285 | 6.99 | 393 | 0.5875 | 0.78 |
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| 0.7953 | 8.0 | 450 | 0.7786 | 0.75 |
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| 0.6224 | 9.0 | 506 | 0.6753 | 0.8 |
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| 0.3806 | 9.99 | 562 | 0.5826 | 0.84 |
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| 0.3121 | 10.99 | 618 | 0.7312 | 0.78 |
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| 0.1729 | 12.0 | 675 | 0.6526 | 0.85 |
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| 0.2958 | 13.0 | 731 | 0.7831 | 0.83 |
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| 0.1496 | 13.99 | 787 | 0.8518 | 0.79 |
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| 0.0659 | 14.99 | 843 | 0.8194 | 0.82 |
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| 0.1208 | 16.0 | 900 | 0.8555 | 0.82 |
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| 0.147 | 17.0 | 956 | 0.6768 | 0.86 |
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| 0.0284 | 17.99 | 1012 | 0.7065 | 0.86 |
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| 0.0295 | 18.99 | 1068 | 0.6942 | 0.87 |
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| 0.0524 | 19.91 | 1120 | nan | 0.86 |
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### Framework versions
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