unlearn_cifar10_resnet-34_neggrad_6_87 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-34_neggrad_6_87

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image-classification

generated_from_trainer

microsoft/resnet-34

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This model is a fine-tuned version of microsoft/resnet-34 on the cifar10 dataset. It achieves the following results on the evaluation set:

Loss: -3.5888
Accuracy: 0.559
Dt Accuracy: 0.559
Df Accuracy: 0.5643
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: 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	-0.1437	0.9897	0.1986	0.1986	None
No log	2.0	48	-0.2039	0.9747	0.2222	0.2222	None
No log	3.0	72	-0.6309	0.8987	0.3300	0.3300	None
No log	4.0	96	-1.3061	0.8577	0.3785	0.3785	None
No log	5.0	120	-1.7955	0.8027	0.4363	0.4363	None
No log	6.0	144	-2.2647	0.7423	0.4859	0.4859	None
No log	7.0	168	-2.6820	0.6757	0.5275	0.5275	None
No log	8.0	192	-3.0834	0.619	0.5515	0.5515	None
No log	9.0	216	-3.2852	0.5897	0.5594	0.5594	None
No log	10.0	240	-3.4582	0.5743	0	0	None
No log	11.0	264	-3.6993	0.566	0	0	None
No log	12.0	288	-3.5888	0.5643	0	0	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2