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--- |
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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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- 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 |
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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: marsyas/gtzan |
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config: all |
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split: train |
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args: all |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.89 |
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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 |
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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: 0.4867 |
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- Accuracy: 0.89 |
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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: 20 |
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- eval_batch_size: 20 |
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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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- 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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| 2.2324 | 1.0 | 45 | 2.1551 | 0.32 | |
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| 1.858 | 2.0 | 90 | 1.7637 | 0.43 | |
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| 1.6808 | 3.0 | 135 | 1.5373 | 0.5 | |
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| 1.4424 | 4.0 | 180 | 1.3738 | 0.59 | |
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| 1.2715 | 5.0 | 225 | 1.1840 | 0.61 | |
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| 1.1501 | 6.0 | 270 | 1.0517 | 0.63 | |
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| 1.0187 | 7.0 | 315 | 0.8796 | 0.72 | |
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| 0.9446 | 8.0 | 360 | 0.8616 | 0.66 | |
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| 0.9266 | 9.0 | 405 | 0.8598 | 0.68 | |
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| 0.7204 | 10.0 | 450 | 0.7464 | 0.72 | |
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| 0.5817 | 11.0 | 495 | 0.7511 | 0.79 | |
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| 0.6758 | 12.0 | 540 | 0.8287 | 0.75 | |
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| 0.5383 | 13.0 | 585 | 0.6391 | 0.8 | |
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| 0.659 | 14.0 | 630 | 0.5670 | 0.84 | |
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| 0.4272 | 15.0 | 675 | 0.6181 | 0.85 | |
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| 0.4661 | 16.0 | 720 | 0.4935 | 0.86 | |
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| 0.4798 | 17.0 | 765 | 0.5827 | 0.85 | |
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| 0.3895 | 18.0 | 810 | 0.4870 | 0.88 | |
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| 0.3039 | 19.0 | 855 | 0.4571 | 0.9 | |
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| 0.2401 | 20.0 | 900 | 0.4867 | 0.89 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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