update to save model results

Code/Results/bert_base_42.txt

+Namespace(architecture='bert-base-uncased', model_type='one', train_dataset='../datasets/data_splits/old_train_semeval.txt', test_dataset='../datasets/data_splits/semeval_test.txt', tokenizer='swp', context=False, masking=False, max_length=512, train_loop='swp', epochs=5, learning_rate=5e-06, random_seed=42, batch_size=16, test_batch_size=64, save_directory='./Results/bert_base_42.txt'){'accuracy': 0.8667400881057269, 'f1': 0.6344410876132931, 'precision': 0.7291666666666666, 'recall': 0.5614973262032086}{'accuracy': 0.9448648648648649, 'f1': 0.8521739130434782, 'precision': 0.9363057324840764, 'recall': 0.7819148936170213}
\ No newline at end of file

Code/main.py

@@ -68,7 +68,12 @@ def run(raw_args):
 	else:
 		print("no eligible train loop selected")
 	#(evaluate... is done internally) but could maybe be implemented here to make average over multiple random seeds
-
+	
+	with open(args.save_directory, "x") as f:
+		f.write(str(args))
+		f.write(str(evaluation_test))
+		f.write(str(evaluation_train))
+	print("saved and done")
 
 if __name__ == "__main__":
 	parser = argparse.ArgumentParser()
@@ -158,6 +163,12 @@ if __name__ == "__main__":
 		type=int,
 		default=64)
 
+	#Save and Organisation
+	parser.add_argument(
+		"-sd",
+		"--save_directory",
+		help="Directory to save run")
+
 	args = parser.parse_args()
 	run(args)