unlearn_cifar10_resnet-50_neggrad_6_87 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-50_neggrad_6_87

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image-classification

generated_from_trainer

microsoft/resnet-50

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This model is a fine-tuned version of microsoft/resnet-50 on the cifar10 dataset. It achieves the following results on the evaluation set:

Loss: -0.1126
Accuracy: 0.9658
Dt Accuracy: 0.9658
Df Accuracy: 0.9843
Unlearn Overall Accuracy: 0.2073
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: 1e-05
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: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	24	-0.1090	0.9863	0.2041	0.2041	None
No log	2.0	48	-0.1103	0.9863	0.2041	0.2041	None
No log	3.0	72	-0.1090	0.9853	0.2057	0.2057	None
No log	4.0	96	-0.1087	0.9857	0.2052	0.2052	None
No log	5.0	120	-0.1105	0.9853	0.2057	0.2057	None
No log	6.0	144	-0.1097	0.9857	0.2052	0.2052	None
No log	7.0	168	-0.1112	0.9837	0.2084	0.2084	None
No log	8.0	192	-0.1127	0.983	0.2094	0.2094	None
No log	9.0	216	-0.1118	0.9833	0.2089	0.2089	None
No log	10.0	240	-0.1124	0.9843	0.2073	0.2073	None
No log	11.0	264	-0.1122	0.984	0.2079	0.2079	None
No log	12.0	288	-0.1126	0.9843	0.2073	0.2073	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2