unlearn_cifar10_resnet-50_neggrad_6_42 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-50_neggrad_6_42

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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: -0.1110
Accuracy: 0.9661
Dt Accuracy: 0.9661
Df Accuracy: 0.9853
Unlearn Overall Accuracy: 0.2057
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: 42
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	-0.1086	0.9877	0.2020	0.2020	None
No log	2.0	48	-0.1091	0.987	0.2030	0.2030	None
No log	3.0	72	-0.1095	0.9867	0.2036	0.2036	None
No log	4.0	96	-0.1097	0.9867	0.2036	0.2036	None
No log	5.0	120	-0.1099	0.987	0.2030	0.2030	None
No log	6.0	144	-0.1112	0.9847	0.2068	0.2068	None
No log	7.0	168	-0.1107	0.9847	0.2068	0.2068	None
No log	8.0	192	-0.1091	0.986	0.2047	0.2047	None
No log	9.0	216	-0.1110	0.985	0.2063	0.2063	None
No log	10.0	240	-0.1119	0.9847	0.2068	0.2068	None
No log	11.0	264	-0.1110	0.9853	0.2057	0.2057	None
No log	12.0	288	-0.1110	0.9853	0.2057	0.2057	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2