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jialicheng/
unlearn-cl_cifar10_swin-base_salun_6_87

Name: unlearn-cl_cifar10_swin-base_salun_6_87
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

endpoints_compatible

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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: 0.0884
Accuracy: 0.9723
Dt Accuracy: 0.9723
Df Accuracy: 0.2047
Unlearn Overall Accuracy: 0.9363
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: 0.0001
train_batch_size: 128
eval_batch_size: 256
seed: 87
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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	0.1053	0.9177	0.3078	0.3078	None
0.4256	2.0	782	0.1184	0.9163	0.3096	0.3096	None
0.4004	3.0	1173	0.1108	0.919	0.3061	0.3061	None
0.3885	4.0	1564	0.1175	0.911	0.3173	0.3173	None
0.3885	5.0	1955	0.0973	0.909	0.3204	0.3204	None
0.3678	6.0	2346	0.1071	0.8767	0.3645	0.3645	None
0.3402	7.0	2737	0.1174	0.8307	0.4234	0.4234	None
0.3261	8.0	3128	0.1283	0.7423	0.5241	0.5241	None
0.2965	9.0	3519	0.1116	0.685	0.5839	0.5839	None
0.2965	10.0	3910	0.1108	0.6347	0.6315	0.6315	None
0.2662	11.0	4301	0.1166	0.5273	0.7219	0.7219	None
0.2476	12.0	4692	0.1126	0.4657	0.7688	0.7688	None
0.2265	13.0	5083	0.1130	0.414	0.8061	0.8061	None
0.2265	14.0	5474	0.1099	0.3247	0.8632	0.8632	None
0.2054	15.0	5865	0.1139	0.286	0.8861	0.8861	None
0.1901	16.0	6256	0.0995	0.2697	0.8982	0.8982	None
0.1729	17.0	6647	0.0986	0.2327	0.9185	0.9185	None
0.1589	18.0	7038	0.0937	0.2293	0.9216	0.9216	None
0.1589	19.0	7429	0.0949	0.2017	0.9370	0.9370	None
0.1499	20.0	7820	0.0884	0.2047	0.9363	0.9363	None

Framework versions

Transformers 4.48.0
Pytorch 2.2.2+cu118
Datasets 3.2.0
Tokenizers 0.21.0

jialicheng/unlearn-cl_cifar10_swin-base_salun_6_87

87

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn-cl_cifar10_swin-base_salun_6_87