def main():
parser = ArgumentParser()
# add task level args
parser = add_task_specific_args(parser)
# add model specific args
parser = Model.add_model_specific_args(parser)
parser = optimization.add_optimizer_specific_args(parser)
parser = Trainer.add_argparse_args(parser)
# set default args
parser.set_defaults(num_labels=13)
args = parser.parse_args()
if args.build_dataset:
build_distill_dataset(args)
else:
common_train(
args,
metric=f'val_{task_info.metric_name}',
model_class=Model,
build_method=build_method,
task=task_info.task_name
)
def main():
parser = ArgumentParser()
# add task level args
parser = add_common_specific_args(parser)
parser = add_tune_specific_args(parser)
parser = add_task_specific_args(parser)
# add model specific args
parser = Model.add_model_specific_args(parser)
parser = optimization.add_optimizer_specific_args(parser)
parser = Trainer.add_argparse_args(parser)
# set default args
parser.set_defaults(gradient_clip_val=1.0, min_epochs=1, max_epochs=10)
parser.set_defaults(num_labels=13)
args = parser.parse_args()
if args.build_dataset:
build_distill_dataset(args)
elif args.tune:
tune_train(args, model_class=Model, task_info=task_info)
else:
common_train(args, model_class=Model, task_info=task_info)