vit_fold_1_v3

nqvii/vit_fold_1_v3

vit_fold_1_v3 is a image classification model from nqvii. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: vit
Access: Public
Created: Aug 9, 2026
Updated: Aug 9, 2026
SHA: 426f44d3

Base models

google/vit-base-patch16-224

Datasets

imagefolder

Model card

From the Hugging Face model README

vit_fold_1_v3

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

Loss: 1.1599
Accuracy: 0.9519
F1 Score: 0.9528
Recall: 0.9537

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: 1e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 150
num_epochs: 100
label_smoothing_factor: 0.15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Score	Recall
2.8856	1.0	20	2.9355	0.2308	0.2215	0.2173
2.6469	2.0	40	2.7349	0.3462	0.3300	0.3278
2.3026	3.0	60	2.4305	0.5385	0.5365	0.5293
1.9124	4.0	80	2.0391	0.7179	0.7186	0.7155
1.5476	5.0	100	1.6601	0.8109	0.8161	0.8111
1.3336	6.0	120	1.4040	0.8910	0.8952	0.8987
1.2139	7.0	140	1.2838	0.9199	0.9223	0.9207
1.1520	8.0	160	1.2277	0.9295	0.9316	0.9306
1.0852	9.0	180	1.2013	0.9455	0.9467	0.9476
1.0903	10.0	200	1.1819	0.9423	0.9436	0.9439
1.0677	11.0	220	1.1724	0.9487	0.9499	0.9513
1.0281	12.0	240	1.1847	0.9487	0.9499	0.9513
1.0140	13.0	260	1.1599	0.9519	0.9528	0.9537
1.0105	14.0	280	1.1549	0.9519	0.9528	0.9537
0.9910	15.0	300	1.1596	0.9519	0.9528	0.9537
0.9909	16.0	320	1.1607	0.9519	0.9525	0.9525
0.9890	17.0	340	1.1589	0.9487	0.9496	0.9501
0.9742	18.0	360	1.1694	0.9487	0.9496	0.9501
0.9855	19.0	380	1.1700	0.9455	0.9467	0.9476
0.9839	20.0	400	1.1701	0.9487	0.9496	0.9501
0.9736	21.0	420	1.1686	0.9487	0.9496	0.9501
0.9678	22.0	440	1.1670	0.9487	0.9496	0.9501
0.9718	23.0	460	1.1681	0.9519	0.9525	0.9525
0.9782	24.0	480	1.1579	0.9519	0.9525	0.9525

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Aug 9, 2026
Updated: Aug 9, 2026