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jialicheng/
unlearn_cifar10_swin-base_salun_8_87

Name: unlearn_cifar10_swin-base_salun_8_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: 0.1210
Accuracy: 0.9651
Dt Accuracy: 0.9651
Df Accuracy: 0.1895
Unlearn Overall Accuracy: 0.9412
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	0.1387	0.9215	0.3026	0.3026	None
0.5176	2.0	782	0.1485	0.9203	0.3042	0.3042	None
0.4753	3.0	1173	0.1473	0.9157	0.3107	0.3107	None
0.4595	4.0	1564	0.1432	0.917	0.3090	0.3090	None
0.4595	5.0	1955	0.1497	0.8795	0.3604	0.3604	None
0.4342	6.0	2346	0.1451	0.8562	0.3911	0.3911	None
0.4066	7.0	2737	0.1353	0.8043	0.4551	0.4551	None
0.38	8.0	3128	0.1580	0.7292	0.5378	0.5378	None
0.3444	9.0	3519	0.1638	0.6228	0.6396	0.6396	None
0.3444	10.0	3910	0.1558	0.5657	0.6895	0.6895	None
0.3071	11.0	4301	0.1419	0.4627	0.7704	0.7704	None
0.278	12.0	4692	0.1393	0.4168	0.8012	0.8012	None
0.2502	13.0	5083	0.1325	0.3478	0.8480	0.8480	None
0.2502	14.0	5474	0.1327	0.3172	0.8659	0.8659	None
0.2306	15.0	5865	0.1444	0.256	0.9012	0.9012	None
0.2067	16.0	6256	0.1378	0.2425	0.9100	0.9100	None
0.1909	17.0	6647	0.1270	0.2182	0.9253	0.9253	None
0.1766	18.0	7038	0.1216	0.2075	0.9314	0.9314	None
0.1766	19.0	7429	0.1238	0.181	0.9452	0.9452	None
0.1653	20.0	7820	0.1210	0.1895	0.9412	0.9412	None

Framework versions

Transformers 4.48.0
Pytorch 2.2.2+cu118
Datasets 3.2.0
Tokenizers 0.21.0

jialicheng/unlearn_cifar10_swin-base_salun_8_87

87

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar10_swin-base_salun_8_87