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
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
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