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jialicheng/
unlearn_cifar100_swin-base_bad_teaching_2_87

Name: unlearn_cifar100_swin-base_bad_teaching_2_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 cifar100 dataset. It achieves the following results on the evaluation set:

Loss: 13.0270
Accuracy: 0.3061
Dt Accuracy: 0.3061
Df Accuracy: 0.194
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: 0.0002
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	Time
No log	1.0	16	1.5558	0.693	None
No log	2.0	32	1.5415	0.686	None
No log	3.0	48	1.8880	0.661	None
No log	4.0	64	2.3622	0.618	None
No log	5.0	80	3.2308	0.529	None
No log	6.0	96	3.3136	0.541	None
No log	7.0	112	3.8720	0.495	None
No log	8.0	128	3.7642	0.509	None
No log	9.0	144	4.3507	0.468	None
No log	10.0	160	5.2100	0.417	None
No log	11.0	176	5.5091	0.397	None
No log	12.0	192	6.1317	0.352	None
No log	13.0	208	6.8544	0.327	None
No log	14.0	224	8.7042	0.29	None
No log	15.0	240	8.6705	0.278	None
No log	16.0	256	8.6764	0.257	None
No log	17.0	272	9.9202	0.241	None
No log	18.0	288	11.7378	0.206	None
No log	19.0	304	11.2166	0.212	None
No log	20.0	320	13.0270	0.194	None

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.18.0
Tokenizers 0.15.2

jialicheng/unlearn_cifar100_swin-base_bad_teaching_2_87

87

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar100_swin-base_bad_teaching_2_87