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jialicheng/
unlearn-cl_cifar10_swin-base_salun_2_87

Name: unlearn-cl_cifar10_swin-base_salun_2_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: 0.0494
Accuracy: 0.9857
Dt Accuracy: 0.9857
Df Accuracy: 0.208
Unlearn Overall Accuracy: 0.9406
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	0.0719	0.925	0.2975	0.2975	None
0.3009	2.0	782	0.0747	0.923	0.3002	0.3002	None
0.2861	3.0	1173	0.0655	0.905	0.3259	0.3259	None
0.2685	4.0	1564	0.0675	0.903	0.3288	0.3288	None
0.2685	5.0	1955	0.0575	0.886	0.3521	0.3521	None
0.2557	6.0	2346	0.0685	0.864	0.3812	0.3812	None
0.2343	7.0	2737	0.0663	0.831	0.4232	0.4232	None
0.2224	8.0	3128	0.0741	0.743	0.5251	0.5251	None
0.2096	9.0	3519	0.0663	0.644	0.6247	0.6247	None
0.2096	10.0	3910	0.0639	0.62	0.6467	0.6467	None
0.1877	11.0	4301	0.0655	0.535	0.7200	0.7200	None
0.1746	12.0	4692	0.0588	0.522	0.7300	0.7300	None
0.1641	13.0	5083	0.0612	0.429	0.8005	0.8005	None
0.1641	14.0	5474	0.0552	0.341	0.8604	0.8604	None
0.1495	15.0	5865	0.0552	0.304	0.8837	0.8837	None
0.136	16.0	6256	0.0533	0.238	0.9226	0.9226	None
0.1281	17.0	6647	0.0512	0.235	0.9254	0.9254	None
0.12	18.0	7038	0.0517	0.211	0.9384	0.9384	None
0.12	19.0	7429	0.0516	0.203	0.9427	0.9427	None
0.1135	20.0	7820	0.0494	0.208	0.9406	0.9406	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_2_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_2_87