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jialicheng/
unlearn_cifar10_swin-base_random_label_10_87

Name: unlearn_cifar10_swin-base_random_label_10_87
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

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87

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the cifar10 dataset. It achieves the following results on the evaluation set:

Loss: 0.1455
Accuracy: 0.9567
Dt Accuracy: 0.9567
Df Accuracy: 0.0758
Unlearn Overall Accuracy: 0
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: 5e-05
train_batch_size: 128
eval_batch_size: 256
seed: 87
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	0.1738	0.9956	0.1889	0.1889	None
0.5193	2.0	782	0.1707	0.994	0.1916	0.1916	None
0.4731	3.0	1173	0.1482	0.9908	0.1969	0.1969	None
0.4554	4.0	1564	0.1329	0.981	0.2126	0.2126	None
0.4554	5.0	1955	0.1510	0.9348	0.2833	0.2833	None
0.4386	6.0	2346	0.1737	0.8226	0.4331	0.4331	None
0.4107	7.0	2737	0.1682	0.7584	0.5073	0.5073	None
0.3892	8.0	3128	0.1804	0.6402	0.6251	0.6251	None
0.3625	9.0	3519	0.1770	0.5122	0.7319	0.7319	None
0.3625	10.0	3910	0.1877	0.3996	0.8094	0.8094	None
0.3339	11.0	4301	0.1496	0.381	0.8262	0.8262	None
0.2993	12.0	4692	0.1470	0.3302	0.8580	0.8580	None
0.2837	13.0	5083	0.1436	0.2628	0.8966	0.8966	None
0.2837	14.0	5474	0.1446	0.2102	0.9272	0.9272	None
0.2641	15.0	5865	0.1535	0.1456	0.9585	0.9585	None
0.2438	16.0	6256	0.1606	0.1066	0.9753	0.9753	None
0.2273	17.0	6647	0.1571	0.0878	0.9752	0.9752	None
0.2187	18.0	7038	0.1524	0.0846	0.9740	0.9740	None
0.2187	19.0	7429	0.1545	0.0726	0	0	None
0.2103	20.0	7820	0.1455	0.0758	0	0	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2

jialicheng/unlearn_cifar10_swin-base_random_label_10_87

87

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar10_swin-base_random_label_10_87