vit-large-HAM-10000-patch-16

ahishamm/vit-large-HAM-10000-patch-16

vit-large-HAM-10000-patch-16 is a image classification model from ahishamm. 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: Jun 27, 2023
Updated: Jun 27, 2023
SHA: dfdfa5a5

Model card

From the Hugging Face model README

vit-large-HAM-10000-patch-16

This model is a fine-tuned version of google/vit-large-patch16-224-in21k on the ahishamm/HAM_db dataset. It achieves the following results on the evaluation set:

Loss: 0.5464
Accuracy: 0.8095
Recall: 0.8095
F1: 0.8095
Precision: 0.8095

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: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	F1	Precision
0.8281	0.2	100	0.9228	0.6788	0.6788	0.6788	0.6788
0.912	0.4	200	0.8353	0.7147	0.7147	0.7147	0.7147
0.6741	0.6	300	0.7841	0.7377	0.7377	0.7377	0.7377
0.8472	0.8	400	0.6710	0.7566	0.7566	0.7566	0.7566
0.7758	1.0	500	0.7587	0.7087	0.7087	0.7087	0.7087
0.5388	1.2	600	0.6607	0.7746	0.7746	0.7746	0.7746
0.5067	1.4	700	0.6133	0.7701	0.7701	0.7701	0.7701
0.4992	1.6	800	0.6075	0.7786	0.7786	0.7786	0.7786
0.5761	1.8	900	0.6286	0.7691	0.7691	0.7691	0.7691
0.5892	2.0	1000	0.5498	0.8035	0.8035	0.8035	0.8035
0.4258	2.2	1100	0.5901	0.7940	0.7940	0.7940	0.7940
0.4066	2.4	1200	0.5553	0.8025	0.8025	0.8025	0.8025
0.3032	2.59	1300	0.5754	0.8030	0.8030	0.8030	0.8030
0.3843	2.79	1400	0.5464	0.8095	0.8095	0.8095	0.8095
0.2679	2.99	1500	0.5683	0.8100	0.8100	0.8100	0.8100
0.1787	3.19	1600	0.5931	0.8195	0.8195	0.8195	0.8195
0.105	3.39	1700	0.6488	0.8279	0.8279	0.8279	0.8279
0.2138	3.59	1800	0.6414	0.8130	0.8130	0.8130	0.8130
0.1336	3.79	1900	0.5920	0.8264	0.8264	0.8264	0.8264
0.1246	3.99	2000	0.5999	0.8289	0.8289	0.8289	0.8289

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Jun 27, 2023
Updated: Jun 27, 2023