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README.md
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---
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license: bsd-3-clause
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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-10-10-0.4593-finetuned-gtzan
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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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# ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
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This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6230
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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: 2
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- eval_batch_size: 2
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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: 10
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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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| 2.1198 | 1.0 | 450 | 1.8429 | 0.47 |
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| 0.0005 | 2.0 | 900 | 1.6282 | 0.71 |
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| 0.3129 | 3.0 | 1350 | 1.0553 | 0.73 |
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| 0.0225 | 4.0 | 1800 | 0.9422 | 0.82 |
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| 0.0025 | 5.0 | 2250 | 0.6008 | 0.85 |
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| 0.0 | 6.0 | 2700 | 0.7194 | 0.86 |
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| 0.0 | 7.0 | 3150 | 0.6268 | 0.89 |
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| 0.0 | 8.0 | 3600 | 0.6372 | 0.89 |
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| 0.0 | 9.0 | 4050 | 0.6167 | 0.89 |
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| 0.0 | 10.0 | 4500 | 0.6230 | 0.89 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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