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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/hubert-base-ls960 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- gtzan |
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metrics: |
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- accuracy |
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model-index: |
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- name: hubert-test-model |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: gtzan |
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type: gtzan |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.785 |
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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-test-model |
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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: 1.5276 |
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- Accuracy: 0.785 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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- mixed_precision_training: Native AMP |
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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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| No log | 1.0 | 150 | 2.0494 | 0.29 | |
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| No log | 2.0 | 300 | 2.1993 | 0.19 | |
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| No log | 3.0 | 450 | 1.8439 | 0.44 | |
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| 1.9218 | 4.0 | 600 | 1.5277 | 0.48 | |
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| 1.9218 | 5.0 | 750 | 1.4164 | 0.475 | |
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| 1.9218 | 6.0 | 900 | 1.3641 | 0.63 | |
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| 1.2685 | 7.0 | 1050 | 1.1557 | 0.675 | |
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| 1.2685 | 8.0 | 1200 | 1.0935 | 0.72 | |
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| 1.2685 | 9.0 | 1350 | 1.0594 | 0.71 | |
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| 0.7151 | 10.0 | 1500 | 1.0119 | 0.735 | |
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| 0.7151 | 11.0 | 1650 | 1.0868 | 0.77 | |
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| 0.7151 | 12.0 | 1800 | 1.3736 | 0.75 | |
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| 0.7151 | 13.0 | 1950 | 1.2705 | 0.77 | |
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| 0.4135 | 14.0 | 2100 | 1.4052 | 0.76 | |
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| 0.4135 | 15.0 | 2250 | 1.3864 | 0.77 | |
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| 0.4135 | 16.0 | 2400 | 1.4296 | 0.785 | |
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| 0.2311 | 17.0 | 2550 | 1.5663 | 0.77 | |
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| 0.2311 | 18.0 | 2700 | 1.5310 | 0.78 | |
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| 0.2311 | 19.0 | 2850 | 1.4884 | 0.795 | |
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| 0.1408 | 20.0 | 3000 | 1.5276 | 0.785 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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