vit-base-patch16-224-FV-20epochs-finetuned-memes

jayanta/vit-base-patch16-224-FV-20epochs-finetuned-memes

vit-base-patch16-224-FV-20epochs-finetuned-memes is a image classification model from jayanta. 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 20, 2022
Updated: Oct 20, 2022
SHA: c8d62e4c

Datasets

imagefolder

Model card

From the Hugging Face model README

vit-base-patch16-224-FV-20epochs-finetuned-memes

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

Loss: 0.6532
Accuracy: 0.8632
Precision: 0.8617
Recall: 0.8632
F1: 0.8621

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: 0.00012
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.1709	0.99	20	0.9393	0.6971	0.6896	0.6971	0.6890
0.5295	1.99	40	0.5024	0.8091	0.8210	0.8091	0.8133
0.2909	2.99	60	0.4070	0.8539	0.8529	0.8539	0.8529
0.1435	3.99	80	0.4136	0.8539	0.8522	0.8539	0.8522
0.0928	4.99	100	0.4495	0.8478	0.8548	0.8478	0.8507
0.0643	5.99	120	0.4897	0.8594	0.8572	0.8594	0.8573
0.061	6.99	140	0.5040	0.8423	0.8490	0.8423	0.8453
0.0519	7.99	160	0.5266	0.8524	0.8502	0.8524	0.8510
0.0546	8.99	180	0.5200	0.8586	0.8632	0.8586	0.8605
0.0478	9.99	200	0.5654	0.8555	0.8548	0.8555	0.8548
0.0509	10.99	220	0.5774	0.8609	0.8626	0.8609	0.8616
0.0467	11.99	240	0.5847	0.8594	0.8602	0.8594	0.8594
0.0468	12.99	260	0.5909	0.8601	0.8597	0.8601	0.8596
0.0469	13.99	280	0.5970	0.8563	0.8560	0.8563	0.8561
0.0438	14.99	300	0.6234	0.8594	0.8583	0.8594	0.8586
0.0441	15.99	320	0.6190	0.8563	0.8582	0.8563	0.8570
0.0431	16.99	340	0.6419	0.8570	0.8584	0.8570	0.8574
0.0454	17.99	360	0.6528	0.8563	0.8556	0.8563	0.8558
0.0417	18.99	380	0.6688	0.8578	0.8575	0.8578	0.8574
0.0432	19.99	400	0.6532	0.8632	0.8617	0.8632	0.8621

Framework versions

Transformers 4.24.0.dev0
Pytorch 1.11.0+cu102
Datasets 2.6.1.dev0
Tokenizers 0.13.1

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Oct 20, 2022
Updated: Oct 20, 2022