unlearn_cifar10_resnet-50_neggrad_10_87 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-50_neggrad_10_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: -0.1370
Accuracy: 0.9572
Dt Accuracy: 0.9572
Df Accuracy: 0.9746
Unlearn Overall Accuracy: 0.2226
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	40	-0.1146	0.9854	0.2056	0.2056	None
No log	2.0	80	-0.1093	0.9854	0.2056	0.2056	None
No log	3.0	120	-0.1122	0.9852	0.2059	0.2059	None
No log	4.0	160	-0.1165	0.9814	0.2119	0.2119	None
No log	5.0	200	-0.1214	0.9802	0.2138	0.2138	None
No log	6.0	240	-0.1211	0.9804	0.2135	0.2135	None
No log	7.0	280	-0.1230	0.979	0.2157	0.2157	None
No log	8.0	320	-0.1262	0.9778	0.2176	0.2176	None
No log	9.0	360	-0.1289	0.977	0.2189	0.2189	None
No log	10.0	400	-0.1403	0.974	0.2235	0.2235	None
No log	11.0	440	-0.1360	0.975	0.2220	0.2220	None
No log	12.0	480	-0.1370	0.9746	0.2226	0.2226	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2