deit-base-patch16-224-FV-finetuned-memes

jayanta/deit-base-patch16-224-FV-finetuned-memes

deit-base-patch16-224-FV-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 21, 2022
Updated: Oct 21, 2022
SHA: 7d0b1c6a

Datasets

imagefolder

Model card

From the Hugging Face model README

deit-base-patch16-224-FV-finetuned-memes

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

Loss: 0.6769
Accuracy: 0.8485
Precision: 0.8458
Recall: 0.8485
F1: 0.8464

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
1.2733	0.99	20	1.0893	0.5811	0.5790	0.5811	0.5293
0.7284	1.99	40	0.7351	0.7210	0.7642	0.7210	0.7271
0.4267	2.99	60	0.5202	0.7991	0.8104	0.7991	0.8033
0.2181	3.99	80	0.4605	0.8346	0.8351	0.8346	0.8334
0.1504	4.99	100	0.5281	0.8253	0.8281	0.8253	0.8266
0.1001	5.99	120	0.4945	0.8369	0.8336	0.8369	0.8347
0.0874	6.99	140	0.5902	0.8338	0.8370	0.8338	0.8348
0.0634	7.99	160	0.6088	0.8253	0.8221	0.8253	0.8234
0.0699	8.99	180	0.6210	0.8207	0.8202	0.8207	0.8186
0.0661	9.99	200	0.5675	0.8385	0.8417	0.8385	0.8393
0.0592	10.99	220	0.6550	0.8253	0.8324	0.8253	0.8275
0.0559	11.99	240	0.6400	0.8416	0.8370	0.8416	0.8387
0.0501	12.99	260	0.6726	0.8393	0.8353	0.8393	0.8350
0.0529	13.99	280	0.6285	0.8408	0.8399	0.8408	0.8401
0.0478	14.99	300	0.6423	0.8400	0.8380	0.8400	0.8384
0.0458	15.99	320	0.6632	0.8369	0.8337	0.8369	0.8348
0.048	16.99	340	0.6719	0.8423	0.8401	0.8423	0.8404
0.0417	17.99	360	0.6807	0.8423	0.8415	0.8423	0.8408
0.0461	18.99	380	0.6732	0.8454	0.8440	0.8454	0.8438
0.044	19.99	400	0.6769	0.8485	0.8458	0.8485	0.8464

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 21, 2022
Updated: Oct 21, 2022