Devarshi/Armature_Defect_Detection_Resin

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ArmatureDefectDetection_Resin

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224-in22k on the imagefolder dataset. It achieves the following results on the evaluation set:

• —Loss: 0.4978
• —Accuracy: 0.76
• —F1: 0.76
• —Recall: 0.76
• —Precision: 0.76

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: 5e-05
• —trainbatchsize: 32
• —evalbatchsize: 32
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 128
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 3

Training results

Framework versions

• —Transformers 4.23.1
• —Pytorch 1.13.0
• —Datasets 2.6.1
• —Tokenizers 0.13.1