remove argmax output

SuperTagger/SuperTagger.py

@@ -161,7 +161,7 @@ class SuperTagger:
 
             preds, hidden = self.model.predict((sents_tokenized_t, sents_mask_t))
 
-            return preds, self.tags_tokenizer.convert_ids_to_tags(preds.detach()), hidden
+            return preds, self.tags_tokenizer.convert_ids_to_tags(torch.argmax(preds, dim=2).detach()), hidden
 
     def train(self, sentences: list[str], tags: list[list[str]], validation_rate=0.1, epochs=20, batch_size=32,
               tensorboard=False,

SuperTagger/Utils/Tagging_bert_model.py

@@ -38,4 +38,4 @@ class Tagging_bert_model(Module):
         output = self.bert(
             input_ids=b_input_ids, attention_mask=b_input_mask)
 
-        return torch.argmax(output[0], dim=2), output[1][0]
+        return output[0], output[1][0]

SuperTagger/Utils/utils.py

@@ -27,5 +27,18 @@ def load_obj(name):
         import pickle
         return pickle.load(f)
 
+def categorical_accuracy_str(preds : list[list[float]], truth: list[list[float]]) -> float:
+    nb_label = 0
+    good_label = 0
+    for i in range(len(truth)):
+        sublist_truth = truth[i]
+        sublist_preds = preds[i]
+        for j in range(min(len(sublist_truth), len(sublist_preds))):
+            if str(sublist_truth[j]) == str(sublist_preds[j]):
+                good_label += 1
+            nb_label += 1
+
+    return good_label / nb_label
+