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--- |
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license: bsd-3-clause |
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base_model: MIT/ast-finetuned-audioset-10-10-0.4593 |
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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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- f1 |
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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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- 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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- name: F1 |
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type: f1 |
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value: 0.89 |
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pipeline_tag: audio-classification |
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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: 0.5658 |
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- Accuracy: 0.87 |
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- F1: 0.87 |
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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: 2024 |
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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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- num_epochs: 10 |
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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 | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
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| 0.8357 | 0.9956 | 56 | 0.6582 | 0.82 | 0.82 | |
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| 0.4742 | 1.9911 | 112 | 0.6527 | 0.81 | 0.81 | |
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| 0.3344 | 2.9867 | 168 | 0.9048 | 0.76 | 0.76 | |
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| 0.0659 | 4.0 | 225 | 0.6998 | 0.84 | 0.8400 | |
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| 0.0966 | 4.9956 | 281 | 0.6737 | 0.83 | 0.83 | |
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| 0.0026 | 5.9911 | 337 | 0.5133 | 0.89 | 0.89 | |
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| 0.0038 | 6.9867 | 393 | 0.5704 | 0.86 | 0.8600 | |
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| 0.0005 | 8.0 | 450 | 0.5722 | 0.86 | 0.8600 | |
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| 0.0003 | 8.9956 | 506 | 0.5632 | 0.87 | 0.87 | |
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| 0.0003 | 9.9556 | 560 | 0.5658 | 0.87 | 0.87 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
