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resume_from_checkpoint_path: null # only used for resume_from_checkpoint option in PL | |
result_path: "./result" | |
pretrained_model_name_or_path: "naver-clova-ix/donut-base" # loading a pre-trained model (from moldehub or path) | |
dataset_name_or_paths: ["./dataset/SGSInvoice"] # loading datasets (from moldehub or path) | |
sort_json_key: False # cord dataset is preprocessed, and publicly available at https://huggingface.co/datasets/naver-clova-ix/cord-v2 | |
train_batch_sizes: [2] | |
val_batch_sizes: [1] | |
input_size: [1280, 960] # when the input resolution differs from the pre-training setting, some weights will be newly initialized (but the model training would be okay) | |
max_length: 768 | |
align_long_axis: False | |
num_nodes: 1 | |
seed: 2022 | |
lr: 3e-5 | |
warmup_steps: 60 # 800/8*30/10, 10% | |
num_training_samples_per_epoch: 800 | |
max_epochs: 10 | |
max_steps: -1 | |
num_workers: 2 | |
val_check_interval: 1.0 | |
check_val_every_n_epoch: 3 | |
gradient_clip_val: 1.0 | |
verbose: True | |