wip

convlab/policy/emoTUS/evaluate.py

@@ -231,7 +231,7 @@ class Evaluator:
 
 
 def emotion_score(golden_emotions, gen_emotions):
-    labels = ["Neutral", "Disappointed", "Dissatisfied",
+    labels = ["Neutral", "Fearful", "Dissatisfied",
               "Apologetic", "Abusive", "Excited", "Satisfied"]
     print(labels)
     macro_f1 = metrics.f1_score(golden_emotions, gen_emotions, average="macro")

convlab/policy/emoTUS/train_model.py

@@ -30,8 +30,8 @@ def arg_parser():
     # data_name, dial_ids_order, split2ratio
     parser.add_argument("--model-type", type=str, default="unify",
                         help="unify or multiwoz")
-    parser.add_argument("--data-name", type=str, default="multiwoz21",
-                        help="multiwoz21, sgd, tm1, tm2, tm3, sgd+tm, or all")
+    parser.add_argument("--data-name", type=str, default="emowoz",
+                        help="emowoz or dialmage")
     parser.add_argument("--dial-ids-order", type=int, default=0)
     parser.add_argument("--split2ratio", type=float, default=1)
     parser.add_argument("--batch-size", type=int, default=16)