unlearn_cifar10_resnet-50_bad_teaching_6_42 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-50_bad_teaching_6_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: 3.0914
Accuracy: 0.7888
Dt Accuracy: 0.7888
Df Accuracy: 0.7953
Unlearn Overall Accuracy: 0.4445
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: 42
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	47	0.1824	0.973	0.2251	0.2251	None
No log	2.0	94	0.3265	0.9543	0.2534	0.2534	None
No log	3.0	141	0.5218	0.9313	0.2866	0.2866	None
No log	4.0	188	0.8913	0.9087	0.3172	0.3172	None
No log	5.0	235	1.4137	0.8653	0.3716	0.3716	None
No log	6.0	282	1.6859	0.8523	0.3865	0.3865	None
No log	7.0	329	2.4252	0.8193	0.4215	0.4215	None
No log	8.0	376	3.0697	0.799	0.4407	0.4407	None
No log	9.0	423	2.8971	0.7977	0.4426	0.4426	None
No log	10.0	470	3.0914	0.7953	0.4445	0.4445	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2