vit-bmr-tuned

pizza883/vit-bmr-tuned

vit-bmr-tuned is a image classification model from pizza883. 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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Hugging Face

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At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: vit
Access: Public
Created: Nov 5, 2025
Updated: Apr 23, 2026
SHA: 968fed72

Base models

google/vit-base-patch16-224-in21k

Datasets

imagefolder

Model card

From the Hugging Face model README

vit-bmr-tuned

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: 0.3154
Accuracy: 0.8519
Precision: 0.8610
Recall: 0.8519
F1: 0.8517

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: 4
eval_batch_size: 8
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
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	160	0.3154	0.8519	0.8610	0.8519	0.8517
No log	2.0	320	0.3871	0.9012	0.9019	0.9012	0.9010
No log	3.0	480	0.5655	0.8765	0.8795	0.8765	0.8759
0.1901	4.0	640	0.5268	0.8765	0.8765	0.8765	0.8765
0.1901	5.0	800	0.5546	0.8765	0.8765	0.8765	0.8765
0.1901	6.0	960	0.5745	0.8765	0.8765	0.8765	0.8765
0.0038	7.0	1120	0.5918	0.8765	0.8765	0.8765	0.8765
0.0038	8.0	1280	0.6056	0.8889	0.8890	0.8889	0.8888
0.0038	9.0	1440	0.6164	0.8765	0.8771	0.8765	0.8763
0.0019	10.0	1600	0.6274	0.8765	0.8771	0.8765	0.8763
0.0019	11.0	1760	0.6356	0.8765	0.8771	0.8765	0.8763
0.0019	12.0	1920	0.6426	0.8765	0.8771	0.8765	0.8763
0.0013	13.0	2080	0.6485	0.8765	0.8771	0.8765	0.8763
0.0013	14.0	2240	0.6529	0.8765	0.8771	0.8765	0.8763
0.0013	15.0	2400	0.6566	0.8765	0.8771	0.8765	0.8763
0.0011	16.0	2560	0.6592	0.8765	0.8771	0.8765	0.8763
0.0011	17.0	2720	0.6610	0.8765	0.8771	0.8765	0.8763
0.0011	18.0	2880	0.6618	0.8765	0.8771	0.8765	0.8763
0.0010	19.0	3040	0.6621	0.8765	0.8771	0.8765	0.8763
0.0010	20.0	3200	0.6622	0.8765	0.8771	0.8765	0.8763

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Nov 5, 2025
Updated: Apr 23, 2026