def main(args):
print_config(args)
set_random_seed(args['random_seed'])
model = ModelHandler(args)
model.train()
model.test()
parser.add_argument('--shuffle', type=str2bool, default=True)
parser.add_argument('--max_epochs', type=int, default=20)
parser.add_argument('--lr', type=float, default=2e-4)
parser.add_argument('--grad_clip', type=float, default=1.0)
parser.add_argument('--verbose',
type=int,
default=200,
help="print after verbose epochs")
parser.add_argument(
'--gradient_accumulation_steps',
type=int,
default=2,
help=
"Number of updates steps to accumulate before performing a backward/update pass."
)
parser.add_argument("--adam_epsilon",
default=1e-8,
type=float,
help="Epsilon for Adam optimizer.")
args = vars(parser.parse_args())
if args['model_name'] == 'SpanBERT':
download_model()
args['model_path'] = 'tmp_'
# TODO: cuda check
handler = ModelHandler(args)
handler.train()
