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vit-base-vocalsound – AI Model by andrei-saceleanu | AlphaNeural AI
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vit-base-vocalsound
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transformers
tf
vit
image-feature-extraction
apache-2.0
endpoints_compatible
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vit-base-vocalsound
This model is a fine-tuned version of
google/vit-base-patch16-224
on
VocalSound
dataset. It achieves the following results on the evaluation set:
accuracy: 81.5
precision (micro): 86.9
recall (micro): 76.4
f1 score (micro): 81.3
f1 score (macro): 81.2
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
Framework versions
Transformers 4.27.4
TensorFlow 2.12.0
Tokenizers 0.13.3
