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()