unlearn_cifar10_resnet-34_salun_6_87 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-34_salun_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: 0.1834
Accuracy: 0.9599
Dt Accuracy: 0.9599
Df Accuracy: 0.875
Unlearn Overall Accuracy: 0.3668
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: 0.0001
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	391	0.2040	0.8753	0.3657	0.3657	None
0.5673	2.0	782	0.2029	0.8937	0.3413	0.3413	None
0.5223	3.0	1173	0.1987	0.8827	0.3564	0.3564	None
0.4908	4.0	1564	0.1939	0.901	0.3313	0.3313	None
0.4908	5.0	1955	0.1943	0.8843	0.3543	0.3543	None
0.47	6.0	2346	0.1863	0.885	0.3534	0.3534	None
0.4371	7.0	2737	0.1895	0.886	0.3521	0.3521	None
0.4282	8.0	3128	0.1851	0.882	0.3575	0.3575	None
0.4099	9.0	3519	0.1853	0.8817	0.3579	0.3579	None
0.4099	10.0	3910	0.1834	0.875	0.3668	0.3668	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2