unlearn_cifar10_resnet-50_neggrad_8_42 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-50_neggrad_8_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: -0.1339
Accuracy: 0.9598
Dt Accuracy: 0.9598
Df Accuracy: 0.975
Unlearn Overall Accuracy: 0.2220
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	32	-0.1086	0.987	0.2030	0.2030	None
No log	2.0	64	-0.1094	0.986	0.2046	0.2046	None
No log	3.0	96	-0.1083	0.9858	0.2050	0.2050	None
No log	4.0	128	-0.1097	0.9868	0.2034	0.2034	None
No log	5.0	160	-0.1118	0.9865	0.2038	0.2038	None
No log	6.0	192	-0.1131	0.9852	0.2058	0.2058	None
No log	7.0	224	-0.1175	0.9825	0.2102	0.2102	None
No log	8.0	256	-0.1208	0.9802	0.2138	0.2138	None
No log	9.0	288	-0.1232	0.9782	0.2169	0.2169	None
No log	10.0	320	-0.1288	0.9762	0.2201	0.2201	None
No log	11.0	352	-0.1324	0.9765	0.2197	0.2197	None
No log	12.0	384	-0.1339	0.975	0.2220	0.2220	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2