vit-tiny-patch16-224-finetuned-papsmear

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

• Loss: 0.2121
• Accuracy: 0.9338

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
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.4005	0.9935	38	1.2214	0.5294
0.8877	1.9869	76	1.0727	0.6691
0.603	2.9804	114	0.6807	0.7574
0.465	4.0	153	0.6485	0.7574
0.432	4.9935	191	0.5024	0.8015
0.2957	5.9869	229	0.4485	0.8162
0.2203	6.9804	267	0.3850	0.8529
0.236	8.0	306	0.3628	0.8456
0.1857	8.9935	344	0.2930	0.8824
0.1907	9.9869	382	0.2121	0.9338
0.1546	10.9804	420	0.2242	0.9265
0.1375	12.0	459	0.1918	0.9191
0.1237	12.9935	497	0.1809	0.9338
0.1637	13.9869	535	0.1774	0.9338
0.0803	14.9020	570	0.1882	0.9338

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 3.0.0
• Tokenizers 0.19.1