vit-weight-decay-1e-5

sharren/vit-weight-decay-1e-5

vit-weight-decay-1e-5 is a image classification model from sharren. 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: Mar 21, 2024
Updated: Mar 21, 2024
SHA: 00854885

Base models

google/vit-base-patch16-224

Model card

From the Hugging Face model README

vit-weight-decay-1e-5

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

Loss: 0.4632
Accuracy: 0.8460
Precision: 0.8510
Recall: 0.8460
F1: 0.8480

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: 0.0001
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: cosine
lr_scheduler_warmup_steps: 1733
num_epochs: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.7624	1.0	321	0.9686	0.7077	0.6754	0.7077	0.6680
1.1455	2.0	642	0.7167	0.7340	0.7348	0.7340	0.7184
1.0313	3.0	963	0.6458	0.7583	0.7586	0.7583	0.7305
0.9864	4.0	1284	0.5631	0.7774	0.7907	0.7774	0.7821
0.931	5.0	1605	0.5847	0.7850	0.7882	0.7850	0.7784
0.9641	6.0	1926	0.5276	0.7899	0.7935	0.7899	0.7906
0.8935	7.0	2247	0.7242	0.7226	0.7970	0.7226	0.7430
0.7589	8.0	2568	0.6404	0.7445	0.7985	0.7445	0.7604
0.7225	9.0	2889	0.5415	0.7975	0.8100	0.7975	0.7986
0.6964	10.0	3210	0.5357	0.7871	0.8323	0.7871	0.8009
0.6232	11.0	3531	0.5579	0.8003	0.8272	0.8003	0.8084
0.5781	12.0	3852	0.6126	0.7847	0.8315	0.7847	0.7978
0.4713	13.0	4173	0.6180	0.8259	0.8343	0.8259	0.8161
0.4834	14.0	4494	0.5668	0.8096	0.8426	0.8096	0.8181
0.3886	15.0	4815	0.4632	0.8460	0.8510	0.8460	0.8480
0.3654	16.0	5136	0.6023	0.8065	0.8375	0.8065	0.8168
0.2904	17.0	5457	0.5002	0.8537	0.8626	0.8537	0.8558
0.2865	18.0	5778	0.5731	0.8332	0.8583	0.8332	0.8408
0.2122	19.0	6099	0.6130	0.8325	0.8606	0.8325	0.8411
0.2227	20.0	6420	0.6097	0.8485	0.8531	0.8485	0.8494
0.179	21.0	6741	0.5650	0.8693	0.8633	0.8693	0.8639
0.1257	22.0	7062	0.5759	0.8714	0.8712	0.8714	0.8707
0.1265	23.0	7383	0.6089	0.8710	0.8684	0.8710	0.8688
0.1146	24.0	7704	0.6169	0.8769	0.8737	0.8769	0.8744
0.1368	25.0	8025	0.5994	0.8745	0.8743	0.8745	0.8739

Framework versions

Transformers 4.40.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Mar 21, 2024
Updated: Mar 21, 2024