unlearn_cifar100_swin-base_random_label_2_42

jialicheng/unlearn_cifar100_swin-base_random_label_2_42

unlearn_cifar100_swin-base_random_label_2_42 is a image classification model from jialicheng. Use it when you need a label for an image.

should probably proofread and complete it, then remove this comment. --

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.safetensors348 MB · 93%

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Base models

microsoft/swin-base-patch4-window7-224

Model card

From the Hugging Face model README

42

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the cifar100 dataset. It achieves the following results on the evaluation set:

Loss: 0.4102
Accuracy: 0.9042
Dt Accuracy: 0.9042
Df Accuracy: 0.025
Unlearn Overall Accuracy: 0.9795
Unlearn Time: None

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: 0.0002
train_batch_size: 128
eval_batch_size: 256
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	391	0.4740	0.871	0.2419	0.2419	None
1.1735	2.0	782	0.4414	0.894	0.2066	0.2066	None
0.9968	3.0	1173	0.4563	0.867	0.2483	0.2483	None
0.8969	4.0	1564	0.4421	0.839	0.2897	0.2897	None
0.8969	5.0	1955	0.4500	0.792	0.3543	0.3543	None
0.8039	6.0	2346	0.4253	0.748	0.4111	0.4111	None
0.7218	7.0	2737	0.4294	0.621	0.5533	0.5533	None
0.646	8.0	3128	0.4357	0.55	0.6211	0.6211	None
0.5839	9.0	3519	0.4262	0.476	0.6867	0.6867	None
0.5839	10.0	3910	0.4365	0.343	0.7868	0.7868	None
0.5275	11.0	4301	0.4485	0.29	0.8229	0.8229	None
0.4966	12.0	4692	0.4309	0.198	0.8822	0.8822	None
0.4474	13.0	5083	0.4520	0.188	0.8859	0.8859	None
0.4474	14.0	5474	0.4439	0.133	0.9186	0.9186	None
0.4102	15.0	5865	0.4377	0.083	0.9458	0.9458	None
0.3744	16.0	6256	0.4364	0.067	0.9545	0.9545	None
0.3453	17.0	6647	0.4343	0.05	0.9629	0.9629	None
0.319	18.0	7038	0.4222	0.048	0.9661	0.9661	None
0.319	19.0	7429	0.4166	0.03	0.9758	0.9758	None
0.3016	20.0	7820	0.4102	0.025	0.9795	0.9795	None

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.18.0
Tokenizers 0.15.2

Task: Image Classification
Type: swin
Created: Oct 22, 2025
Updated: Oct 22, 2025