unlearn_cifar100_swin-base_random_label_6_42

jialicheng/unlearn_cifar100_swin-base_random_label_6_42

unlearn_cifar100_swin-base_random_label_6_42 is a image classification model from jialicheng. Use it when you need a label for an image. 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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.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: 0.4605
Accuracy: 0.887
Dt Accuracy: 0.887
Df Accuracy: 0.0247
Unlearn Overall Accuracy: 0.9709
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	0.5295	0.8873	0.2167	0.2167	None
1.3324	2.0	782	0.4877	0.891	0.2113	0.2113	None
1.1366	3.0	1173	0.5020	0.877	0.2331	0.2331	None
1.0197	4.0	1564	0.4836	0.851	0.2724	0.2724	None
1.0197	5.0	1955	0.4607	0.8253	0.3092	0.3092	None
0.9076	6.0	2346	0.4997	0.7397	0.4201	0.4201	None
0.8133	7.0	2737	0.4802	0.627	0.5457	0.5457	None
0.7391	8.0	3128	0.4875	0.5163	0.6491	0.6491	None
0.6743	9.0	3519	0.5113	0.4307	0.7164	0.7164	None
0.6743	10.0	3910	0.5024	0.3383	0.7846	0.7846	None
0.6002	11.0	4301	0.5063	0.258	0.8351	0.8351	None
0.551	12.0	4692	0.4918	0.214	0.8641	0.8641	None
0.5027	13.0	5083	0.4968	0.1667	0.8918	0.8918	None
0.5027	14.0	5474	0.4826	0.1327	0.9110	0.9110	None
0.454	15.0	5865	0.4752	0.0963	0.9312	0.9312	None
0.4188	16.0	6256	0.4738	0.0657	0.9479	0.9479	None
0.3824	17.0	6647	0.4686	0.0437	0.9599	0.9599	None
0.3579	18.0	7038	0.4766	0.028	0.9672	0.9672	None
0.3579	19.0	7429	0.4646	0.0267	0.9694	0.9694	None
0.3325	20.0	7820	0.4605	0.0247	0.9709	0.9709	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
License: apache-2.0
Created: Oct 22, 2025
Updated: Oct 22, 2025