emotion-vit – AI Model by saccanip | AlphaNeural AI

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saccanip/
emotion-vit

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image-classification

generated_from_trainer

google/vit-base-patch16-224

autotrain_compatible

endpoints_compatible

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results

This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.2708
Accuracy: 0.625

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.7925	1.0	80	1.2881	0.5625
0.8274	2.0	160	1.2765	0.525
0.3026	3.0	240	1.1460	0.55
0.0789	4.0	320	1.1513	0.5938
0.0204	5.0	400	1.2303	0.5938
0.0178	6.0	480	1.2826	0.6188
0.0118	7.0	560	1.2708	0.625
0.0089	8.0	640	1.2886	0.6188
0.0107	9.0	720	1.3031	0.6062
0.0086	10.0	800	1.3060	0.6062

Framework versions

Transformers 4.48.3
Pytorch 2.5.1+cu124
Tokenizers 0.21.0