---
license: apache-2.0
model-index:
- name: vit-base-vocalsound-logmel
  results: []
---

# vit-base-vocalsound-logmel

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.
It achieves the following results on the evaluation set:

- accuracy: 88.8
- precision (micro): 91.3
- recall (micro): 87.1
- f1 score (micro): 89.1
- f1 score (macro): 89.1

## Training and evaluation data

Training: VocalSound training split (#samples = 15570)

Evaluation: VocalSound test split(#samples = 3594)

### Training hyperparameters

The following hyperparameters were used during training:
- optimizer: AdamW
  - weight_decay: 0
  - learning_rate: 5e-5
- batch_size: 32
- training_precision: float32

### Preprocessing

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
step uses VocalSound statistics(i.e. mean and std) instead of the default IMAGENET ones.

### Framework versions

- Transformers 4.27.4
- TensorFlow 2.12.0
- Tokenizers 0.13.3