unlearn_cifar10_resnet-34_neggrad_8_42 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-34_neggrad_8_42

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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: -6.1734
Accuracy: 0.4633
Dt Accuracy: 0.4633
Df Accuracy: 0.4718
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: 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	-0.1475	0.9898	0.1985	0.1985	None
No log	2.0	64	-0.3224	0.9503	0.2590	0.2590	None
No log	3.0	96	-1.3843	0.8203	0.4182	0.4182	None
No log	4.0	128	-2.7740	0.7192	0.5003	0.5003	None
No log	5.0	160	-3.7965	0.6378	0.5409	0.5409	None
No log	6.0	192	-4.6399	0.5607	0	0	None
No log	7.0	224	-5.2912	0.5198	0	0	None
No log	8.0	256	-5.6292	0.5075	0	0	None
No log	9.0	288	-5.7188	0.4935	0	0	None
No log	10.0	320	-5.8928	0.4843	0	0	None
No log	11.0	352	-6.1721	0.4755	0	0	None
No log	12.0	384	-6.1734	0.4718	0	0	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2