vit-bmr-augmented

jmoriwa/vit-bmr-augmented

vit-bmr-augmented is a image classification model from jmoriwa. 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: Oct 29, 2025
Updated: Oct 29, 2025
SHA: 61e3e277

Base models

google/vit-base-patch16-224-in21k

Datasets

imagefolder

Model card

From the Hugging Face model README

vit-bmr-augmented

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: 0.5922
Accuracy: 0.6667
Precision: 0.6663
Recall: 0.6667
F1: 0.6664

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: 0.0002
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: linear
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	160	0.6951	0.4691	0.2201	0.4691	0.2996
No log	2.0	320	0.6841	0.5309	0.2818	0.5309	0.3682
No log	3.0	480	0.6859	0.5802	0.6735	0.5802	0.5354
0.7037	4.0	640	0.6921	0.5309	0.2818	0.5309	0.3682
0.7037	5.0	800	0.6910	0.5309	0.2818	0.5309	0.3682
0.7037	6.0	960	0.6660	0.7037	0.7180	0.7037	0.6941
0.6949	7.0	1120	0.6931	0.4691	0.2201	0.4691	0.2996
0.6949	8.0	1280	0.7131	0.4691	0.2201	0.4691	0.2996
0.6949	9.0	1440	0.6832	0.5432	0.7545	0.5432	0.3952
0.69	10.0	1600	0.5922	0.6667	0.6663	0.6667	0.6664
0.69	11.0	1760	0.7749	0.6543	0.7011	0.6543	0.6417
0.69	12.0	1920	0.6127	0.6914	0.6919	0.6914	0.6915
0.5014	13.0	2080	0.8927	0.6914	0.7115	0.6914	0.6882
0.5014	14.0	2240	0.8250	0.7284	0.7298	0.7284	0.7286
0.5014	15.0	2400	0.8753	0.7284	0.7298	0.7284	0.7286

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Oct 29, 2025
Updated: Oct 29, 2025