from .pretrain import * | |
del available_corpus | |
train_file = [ | |
f"{anno_root_downstream}/tvqa_train_with_answer.json", | |
f"{data_root}/tvqa_trimmed_3fps", | |
"video", | |
] | |
test_file = dict( | |
val=[ | |
f"{anno_root_downstream}/tvqa_val_with_answer.json", | |
f"{data_root}/tvqa_trimmed_3fps", | |
"video", | |
], | |
test=[ | |
f"{anno_root_downstream}/tvqa_test_public_with_answer.json", | |
f"{data_root}/tvqa_trimmed_3fps", | |
"video", | |
], | |
) | |
test_types = ["val"] | |
stop_key = "val" # used to choose the best ckpt. If None, save the last. | |
is_paragraph_retrieval = False | |
criterion["loss_weight"]["mlm"] = 0.0 | |
optimizer["lr"] = 1e-5 | |
scheduler["warmup_epochs"] = 0.5 | |
scheduler["epochs"] = 10 | |
max_txt_l = 150 | |
batch_size = 32 | |
num_frames = 12 | |
log_freq = 100 | |