FFPP-Raw_1FPS_faces-expand-0-aligned_augmentation-normalize-image-mean-std

hchcsuim/FFPP-Raw_1FPS_faces-expand-0-aligned_augmentation-normalize-image-mean-std

FFPP-Raw_1FPS_faces-expand-0-aligned_augmentation-normalize-image-mean-std is a image classification model from hchcsuim. 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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Hugging Face

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.safetensors110 MB · 99%

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Base models

microsoft/swin-tiny-patch4-window7-224

Datasets

imagefolder

Model card

From the Hugging Face model README

FFPP-Raw_1FPS_faces-expand-0-aligned_augmentation-normalize-image-mean-std

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0034
Accuracy: 0.9983
Recall: 0.9929
Precision: 0.9994
F1: 0.9961
Roc Auc: 1.0000

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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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	Recall	Precision	F1	Roc Auc
0.1054	1.0	1377	0.0750	0.9716	0.9180	0.9495	0.9335	0.9957
0.0785	2.0	2755	0.0406	0.9853	0.9596	0.9723	0.9660	0.9986
0.0713	3.0	4132	0.0348	0.9878	0.9534	0.9899	0.9713	0.9994
0.0447	4.0	5510	0.0172	0.9933	0.9842	0.9851	0.9846	0.9997
0.0388	5.0	6887	0.0186	0.9936	0.9741	0.9964	0.9851	0.9998
0.0236	6.0	8265	0.0119	0.9957	0.9830	0.9971	0.9900	0.9999
0.031	7.0	9642	0.0137	0.9957	0.9928	0.9873	0.9900	0.9999
0.015	8.0	11020	0.0072	0.9972	0.9903	0.9969	0.9936	1.0000
0.0429	9.0	12397	0.0087	0.9967	0.9863	0.9987	0.9925	0.9999
0.0186	10.0	13775	0.0052	0.9979	0.9919	0.9985	0.9952	1.0000
0.0282	11.0	15152	0.0069	0.9974	0.9892	0.9988	0.9940	1.0000
0.0034	12.0	16530	0.0045	0.9979	0.9947	0.9956	0.9951	1.0000
0.0187	13.0	17907	0.0070	0.9972	0.9886	0.9986	0.9935	1.0000
0.0136	14.0	19285	0.0038	0.9982	0.9931	0.9988	0.9959	1.0000
0.006	15.0	20662	0.0039	0.9982	0.9928	0.9988	0.9958	1.0000
0.0067	16.0	22040	0.0037	0.9983	0.9926	0.9995	0.9960	1.0000
0.0121	17.0	23417	0.0036	0.9983	0.9929	0.9992	0.9960	1.0000
0.0026	18.0	24795	0.0037	0.9982	0.9925	0.9993	0.9959	1.0000
0.0024	19.0	26172	0.0034	0.9983	0.9932	0.9991	0.9961	1.0000
0.002	19.99	27540	0.0034	0.9983	0.9929	0.9994	0.9961	1.0000

Framework versions

Transformers 4.39.2
Pytorch 2.2.2
Datasets 2.18.0
Tokenizers 0.15.2

Task: Image Classification
Library: transformers
Type: swin
License: apache-2.0
Created: Apr 12, 2024
Updated: Apr 13, 2024