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defaults:
- _self_
- train/lr_scheduler: step
- train/optimizer: adam
mode: train
img_size: [448,448]
max_seq_len: 512
label_type: html+cell+bbox
train:
target: ${trainer.label_type}
img_size: ${trainer.img_size}
loss_weights:
table: 0
html: 0
cell: 0
bbox: 0
grad_clip: 5
epochs: 24
save_every: 1
max_seq_len: ${trainer.max_seq_len}
dataloader:
_target_: src.datamodule.dataloader_html
batch_size: 48
label_type: ${trainer.label_type}
valid:
target: ${trainer.label_type}
img_size: ${trainer.img_size}
loss_weights: ${trainer.train.loss_weights}
max_seq_len: ${trainer.max_seq_len}
dataloader:
_target_: src.datamodule.dataloader_html
batch_size: 48
label_type: ${trainer.label_type}
test:
target: ${trainer.train.target}
img_size: ${trainer.img_size}
loss_weights: ${trainer.train.loss_weights}
metrics: teds
max_seq_len: ${trainer.max_seq_len}
sampling: greedy
save_to_prefix: html_table_result
dataloader:
_target_: src.datamodule.dataloader_html
batch_size: 96
label_type: ${trainer.label_type}
trainer:
_target_: src.trainer.TableTrainer
snapshot: null
model_weights: null
beit_pretrained_weights: null
freeze_beit_epoch: null |