vit-weight-decay-1e-2

sharren/vit-weight-decay-1e-2

vit-weight-decay-1e-2 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: ee979e5e

Base models

google/vit-base-patch16-224

Model card

From the Hugging Face model README

vit-weight-decay-1e-2

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: 0.4994
Accuracy: 0.8603
Precision: 0.8618
Recall: 0.8603
F1: 0.8600

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: 1219
num_epochs: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.7124	1.0	321	0.8697	0.6924	0.6656	0.6924	0.6030
1.1476	2.0	642	0.7271	0.6990	0.7684	0.6990	0.7149
1.0734	3.0	963	0.6441	0.7687	0.7568	0.7687	0.7417
1.0271	4.0	1284	0.5855	0.7774	0.7883	0.7774	0.7814
0.9158	5.0	1605	0.7002	0.7635	0.7930	0.7635	0.7662
0.9167	6.0	1926	0.5867	0.7812	0.8065	0.7812	0.7900
0.786	7.0	2247	0.6517	0.7340	0.8047	0.7340	0.7515
0.7406	8.0	2568	0.6647	0.7067	0.8134	0.7067	0.7330
0.682	9.0	2889	0.5106	0.8228	0.8231	0.8228	0.8207
0.6427	10.0	3210	0.5032	0.8166	0.8354	0.8166	0.8222
0.5663	11.0	3531	0.5358	0.8152	0.8326	0.8152	0.8216
0.5395	12.0	3852	0.5488	0.8249	0.8392	0.8249	0.8299
0.4468	13.0	4173	0.5790	0.8232	0.8397	0.8232	0.8260
0.4247	14.0	4494	0.5438	0.8415	0.8570	0.8415	0.8449
0.3495	15.0	4815	0.5135	0.8454	0.8519	0.8454	0.8467
0.3039	16.0	5136	0.5631	0.8408	0.8520	0.8408	0.8448
0.2602	17.0	5457	0.4994	0.8603	0.8618	0.8603	0.8600
0.2616	18.0	5778	0.5406	0.8564	0.8622	0.8564	0.8585
0.1876	19.0	6099	0.5612	0.8481	0.8629	0.8481	0.8525
0.2052	20.0	6420	0.6803	0.8429	0.8502	0.8429	0.8428
0.1533	21.0	6741	0.5464	0.8734	0.8698	0.8734	0.8709
0.1175	22.0	7062	0.5573	0.8686	0.8667	0.8686	0.8673
0.1218	23.0	7383	0.6043	0.8703	0.8681	0.8703	0.8669
0.114	24.0	7704	0.5945	0.8710	0.8706	0.8710	0.8693
0.104	25.0	8025	0.5850	0.8766	0.8753	0.8766	0.8752
0.0752	26.0	8346	0.5868	0.8783	0.8747	0.8783	0.8757
0.1309	27.0	8667	0.5839	0.8786	0.8753	0.8786	0.8761

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