vit-base-patch16-224-finetuned-barkley

alyzbane/vit-base-patch16-224-finetuned-barkley

vit-base-patch16-224-finetuned-barkley is a image classification model from alyzbane. 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 17, 2024
Updated: Oct 29, 2024
SHA: 6ad6adf7

Base models

google/vit-base-patch16-224

Model card

From the Hugging Face model README

vit-base-patch16-224-finetuned-barkley

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

Loss: 0.0036
Precision: 1.0
Recall: 1.0
F1: 1.0
Accuracy: 1.0
Top1 Accuracy: 1.0
Error Rate: 0.0

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: 0.0005
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: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy	Top1 Accuracy	Error Rate
1.6093	1.0	38	1.4340	0.4769	0.4342	0.4066	0.4149	0.4342	0.5851
1.2908	2.0	76	1.1747	0.6587	0.6118	0.6160	0.6161	0.6118	0.3839
1.0409	3.0	114	0.9174	0.7382	0.7303	0.7293	0.7425	0.7303	0.2575
0.781	4.0	152	0.6528	0.8632	0.8618	0.8622	0.8650	0.8618	0.1350
0.5429	5.0	190	0.4112	0.9417	0.9408	0.9405	0.9443	0.9408	0.0557
0.328	6.0	228	0.2229	0.9809	0.9803	0.9802	0.9811	0.9803	0.0189
0.1837	7.0	266	0.1181	0.9871	0.9868	0.9868	0.9878	0.9868	0.0122
0.1131	8.0	304	0.0680	0.9937	0.9934	0.9934	0.9944	0.9934	0.0056
0.0526	9.0	342	0.0387	0.9937	0.9934	0.9934	0.9944	0.9934	0.0056
0.0283	10.0	380	0.0328	0.9873	0.9868	0.9869	0.9878	0.9868	0.0122
0.019	11.0	418	0.0224	0.9873	0.9868	0.9868	0.9889	0.9868	0.0111
0.0148	12.0	456	0.0201	0.9873	0.9868	0.9868	0.9889	0.9868	0.0111
0.0095	13.0	494	0.0396	0.9871	0.9868	0.9868	0.9878	0.9868	0.0122
0.007	14.0	532	0.0048	1.0	1.0	1.0	1.0	1.0	0.0
0.011	15.0	570	0.0036	1.0	1.0	1.0	1.0	1.0	0.0
0.0071	16.0	608	0.0092	0.9936	0.9934	0.9934	0.9941	0.9934	0.0059
0.0103	17.0	646	0.0148	0.9936	0.9934	0.9934	0.9944	0.9934	0.0056

Framework versions

Transformers 4.44.2
Pytorch 2.3.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Oct 17, 2024
Updated: Oct 29, 2024