google-vit-base-patch16-224-cartoon-face-recognition

jayanta/google-vit-base-patch16-224-cartoon-face-recognition

google-vit-base-patch16-224-cartoon-face-recognition 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: Jan 18, 2023
Updated: Jan 18, 2023
SHA: cb74788e

Datasets

imagefolder

Spaces

zzzsy/jayanta-google-vit-base-patch16-224-cartoon-face-recognition

Model card

From the Hugging Face model README

google-vit-base-patch16-224-cartoon-face-recognition

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: 0.3707
Accuracy: 0.9005
Precision: 0.9066
Recall: 0.9005
F1: 0.8984

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
No log	0.89	6	0.5459	0.8611	0.8683	0.8611	0.8577
0.0812	1.89	12	0.4703	0.8796	0.8833	0.8796	0.8764
0.0812	2.89	18	0.4430	0.8935	0.8969	0.8935	0.8906
0.0307	3.89	24	0.4045	0.8819	0.8849	0.8819	0.8767
0.0091	4.89	30	0.3672	0.9005	0.9025	0.9005	0.8980
0.0091	5.89	36	0.3841	0.9028	0.9125	0.9028	0.9011
0.0043	6.89	42	0.3926	0.9005	0.9073	0.9005	0.8972
0.0043	7.89	48	0.3786	0.8958	0.9005	0.8958	0.8931
0.0031	8.89	54	0.3791	0.9028	0.9091	0.9028	0.9007
0.002	9.89	60	0.3677	0.9028	0.9106	0.9028	0.9001
0.002	10.89	66	0.3740	0.9028	0.9099	0.9028	0.9007
0.0027	11.89	72	0.3869	0.8981	0.9043	0.8981	0.8956
0.0027	12.89	78	0.3801	0.8981	0.9021	0.8981	0.8954
0.004	13.89	84	0.3674	0.9051	0.9113	0.9051	0.9028
0.0024	14.89	90	0.3620	0.9051	0.9096	0.9051	0.9027
0.0024	15.89	96	0.3670	0.9028	0.9089	0.9028	0.9006
0.0021	16.89	102	0.3827	0.9005	0.9065	0.9005	0.8980
0.0021	17.89	108	0.3748	0.8981	0.9049	0.8981	0.8958
0.0022	18.89	114	0.3825	0.9028	0.9101	0.9028	0.9006
0.0019	19.89	120	0.3707	0.9005	0.9066	0.9005	0.8984

Framework versions

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

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Jan 18, 2023
Updated: Jan 18, 2023