yangswei/visual-emotion-classification

image_classification

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 1.1599
• Accuracy: 0.5813

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 13

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	40	1.8887	0.35
No log	2.0	80	1.5494	0.425
No log	3.0	120	1.4015	0.5188
No log	4.0	160	1.2919	0.55
No log	5.0	200	1.2205	0.5813
No log	6.0	240	1.2246	0.575
No log	7.0	280	1.2053	0.5312
No log	8.0	320	1.1487	0.5687
No log	9.0	360	1.1727	0.5437
No log	10.0	400	1.1459	0.55
No log	11.0	440	1.1313	0.5813
No log	12.0	480	1.0990	0.6062
1.1138	13.0	520	1.1020	0.6188

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1