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: 1.2152
• Accuracy: 0.5687

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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	40	1.3484	0.5437
No log	2.0	80	1.3268	0.4875
No log	3.0	120	1.2463	0.5437
No log	4.0	160	1.2361	0.5563
No log	5.0	200	1.2089	0.5813
No log	6.0	240	1.2544	0.525
No log	7.0	280	1.1947	0.5563
No log	8.0	320	1.2502	0.5188
No log	9.0	360	1.3415	0.4938
No log	10.0	400	1.1336	0.6
No log	11.0	440	1.2716	0.5437
No log	12.0	480	1.4631	0.5
0.6882	13.0	520	1.3970	0.5563
0.6882	14.0	560	1.2654	0.5188
0.6882	15.0	600	1.2498	0.575
0.6882	16.0	640	1.2655	0.5938
0.6882	17.0	680	1.3577	0.55
0.6882	18.0	720	1.2711	0.5813
0.6882	19.0	760	1.3127	0.5687
0.6882	20.0	800	1.2478	0.575

Framework versions

• Transformers 4.33.2
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3