Commented unnecessary code

classifier/nn.py

@@ -104,10 +104,10 @@ class BiLstmClassifier(Model):
         output_dict['probabilities'] = class_probabilities
         output_dict['positive_label'] = label
         output_dict['prediction'] = label
-        citation_text = []
-        for batch_text in output_dict['tokens']:
-            citation_text.append([self.vocab.get_token_from_index(token_id.item()) for token_id in batch_text])
-        output_dict['tokens'] = citation_text
+        # citation_text = []
+        # for batch_text in output_dict['tokens']:
+        #     citation_text.append([self.vocab.get_token_from_index(token_id.item()) for token_id in batch_text])
+        # output_dict['tokens'] = citation_text
 
         return output_dict
 

configs/basic_model.json

@@ -49,9 +49,9 @@
   "trainer": {
     "optimizer": {
       "type": "adagrad",
-      "lr": 0.001
+      "lr": 0.005
     },
-    "num_epochs": 20,
+    "num_epochs": 10,
     "cuda_device": 3
   }
 }

testing/intent_predictor.py

@@ -41,8 +41,9 @@ def make_predictions(model: Model, dataset_reader: DatasetReader, file_path: str
         i += 1
         true_list.append(citation.intent)
         output = predictor.predict(citation.text, citation.intent)
-        prediction_list.append({vocab.get_token_from_index(label_id, 'labels'): prob
-                                for label_id, prob in enumerate(output['probs'])})
+        prediction_list.append(output['prediction'])
+        # prediction_list.append({vocab.get_token_from_index(label_id, 'labels'): prob
+        #                         for label_id, prob in enumerate(output['probabilities'])})
         if i == 10:
             break
 
@@ -59,4 +60,5 @@ def load_model_and_run_predictions(saved_model_dir: str):
 
     y_pred, y_true = make_predictions(model_archive.model, citation_dataset_reader, test_file_path)
 
-    print(y_pred)
+    print('Predictions ', y_pred)
+    print('True Labels ', y_true)