ConvNeXt for Face Mask Detection

ConvNeXt model pre-trained and fine-tuned on Self Currated Custom Face-Mask18K Dataset (18k images, 2 classes) at resolution 224x224. It was introduced in the paper A ConvNet for the 2020s by Zhuang Liu, Hanzi Mao et al.

Training Metrics

epoch                    =         3.54
total_flos               = 1195651761GF
train_loss               =       0.0079
train_runtime            =   1:08:20.25
train_samples_per_second =       14.075
train_steps_per_second   =         0.22

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Evaluation Metrics

epoch                   =       3.54
eval_accuracy           =     0.9961
eval_loss               =     0.0151
eval_runtime            = 0:01:23.47
eval_samples_per_second =     43.079
eval_steps_per_second   =      5.391