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# data
augmentations: 'vit_heavy'
image_size: [256, 256] # [height, width]
dataset: 'SnakeCLEF2023'
# model
architecture: 'swinv2_tiny_window16_256.ms_in1k'
# training
loss: 'SeeSawLoss'
optimizer: 'SGD'
scheduler: 'plateau'
epochs: 100
learning_rate: 0.01
batch_size: 32
accumulation_steps: 4
# other
random_seed: 777
workers: 1
multigpu: False
tags: ["Fine-tuning"] # W&B Run tags
root_path: "./" |