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license: apache-2.0 |
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model-index: |
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- name: vit-base-vocalsound-logmel |
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results: [] |
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--- |
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# vit-base-vocalsound-logmel |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on [VocalSound](https://github.com/YuanGongND/vocalsound) dataset. |
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It achieves the following results on the evaluation set: |
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- accuracy: 88.8 |
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- precision (micro): 91.3 |
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- recall (micro): 87.1 |
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- f1 score (micro): 89.1 |
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- f1 score (macro): 89.1 |
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## Training and evaluation data |
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Training: VocalSound training split (#samples = 15570) |
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Evaluation: VocalSound test split(#samples = 3594) |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: AdamW |
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- weight_decay: 0 |
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- learning_rate: 5e-5 |
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- batch_size: 32 |
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- training_precision: float32 |
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### Preprocessing |
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Differently from [vit-base-vocalsound](https://huggingface.co/andrei-saceleanu/vit-base-vocalsound), the log-melspectrogram is used(log was applied as an addition) and the preprocessor normalization |
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step uses VocalSound statistics(i.e. mean and std) instead of the default IMAGENET ones. |
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### Framework versions |
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- Transformers 4.27.4 |
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- TensorFlow 2.12.0 |
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- Tokenizers 0.13.3 |
