You can deploy this model and start earning money today!

jialicheng/
unlearn-cl_cifar10_swin-base_random_label_10_42

Name: unlearn-cl_cifar10_swin-base_random_label_10_42
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

endpoints_compatible

Views

No views yet

42

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: 0.1389
Accuracy: 0.9534
Dt Accuracy: 0.9534
Df Accuracy: 0.07
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: 42
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	0.1540	0.9952	0.1896	0.1896	None
0.4761	2.0	782	0.1364	0.993	0.1932	0.1932	None
0.4391	3.0	1173	0.1318	0.991	0.1965	0.1965	None
0.4274	4.0	1564	0.1234	0.9822	0.2107	0.2107	None
0.4274	5.0	1955	0.1493	0.9264	0.2954	0.2954	None
0.4046	6.0	2346	0.1367	0.8708	0.3722	0.3722	None
0.3839	7.0	2737	0.1590	0.734	0.5333	0.5333	None
0.3566	8.0	3128	0.1435	0.6492	0.6173	0.6173	None
0.3362	9.0	3519	0.1611	0.5392	0.7088	0.7088	None
0.3362	10.0	3910	0.1735	0.3868	0.8189	0.8189	None
0.3084	11.0	4301	0.1751	0.3088	0.8664	0.8664	None
0.2842	12.0	4692	0.1505	0.308	0.8692	0.8692	None
0.2608	13.0	5083	0.1441	0.2378	0.9115	0.9115	None
0.2608	14.0	5474	0.1517	0.1848	0.9371	0.9371	None
0.2411	15.0	5865	0.1483	0.1446	0.9574	0.9574	None
0.2276	16.0	6256	0.1404	0.1132	0.9751	0.9751	None
0.2132	17.0	6647	0.1478	0.0904	0.9749	0.9749	None
0.1978	18.0	7038	0.1499	0.0766	0	0	None
0.1978	19.0	7429	0.1426	0.0672	0	0	None
0.1919	20.0	7820	0.1389	0.07	0	0	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_random_label_10_42

42

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn-cl_cifar10_swin-base_random_label_10_42