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--- |
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license: bsd-3-clause |
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base_model: MIT/ast-finetuned-audioset-10-10-0.450 |
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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: ast-finetuned-audioset-10-10-0.450-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: 0.88 |
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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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# ast-finetuned-audioset-10-10-0.450-finetuned-gtzan |
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This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.450](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.450) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4457 |
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- Accuracy: 0.88 |
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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: 16 |
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- eval_batch_size: 16 |
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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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| 0.5804 | 1.0 | 57 | 0.5356 | 0.84 | |
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| 0.2655 | 2.0 | 114 | 0.5664 | 0.76 | |
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| 0.1767 | 3.0 | 171 | 0.3925 | 0.88 | |
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| 0.4169 | 4.0 | 228 | 0.8874 | 0.78 | |
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| 0.0685 | 5.0 | 285 | 0.6067 | 0.83 | |
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| 0.0725 | 6.0 | 342 | 0.5612 | 0.81 | |
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| 0.1003 | 7.0 | 399 | 0.6928 | 0.82 | |
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| 0.004 | 8.0 | 456 | 0.4814 | 0.86 | |
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| 0.0122 | 9.0 | 513 | 0.6141 | 0.86 | |
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| 0.0009 | 10.0 | 570 | 0.4017 | 0.91 | |
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| 0.0828 | 11.0 | 627 | 0.4937 | 0.88 | |
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| 0.0025 | 12.0 | 684 | 0.8455 | 0.82 | |
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| 0.0005 | 13.0 | 741 | 0.4439 | 0.89 | |
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| 0.0001 | 14.0 | 798 | 0.4956 | 0.87 | |
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| 0.0001 | 15.0 | 855 | 0.4362 | 0.88 | |
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| 0.0001 | 16.0 | 912 | 0.4146 | 0.89 | |
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| 0.0299 | 17.0 | 969 | 0.4241 | 0.9 | |
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| 0.0001 | 18.0 | 1026 | 0.4375 | 0.87 | |
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| 0.0001 | 19.0 | 1083 | 0.4502 | 0.88 | |
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| 0.0001 | 20.0 | 1140 | 0.4457 | 0.88 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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