edit train

train.py

@@ -33,6 +33,11 @@ from flair.embeddings import TransformerDocumentEmbeddings
 #model = "HooshvareLab/bert-base-parsbert-peymaner-uncased" # جالب نبود!
 #model = "HooshvareLab/bert-base-parsbert-armanner-uncased" # جالب نبود!
 
+def digit_correct(input_num):
+    if input_num <10:
+        return f'0{input_num}'
+    return str(input_num)
+
 def main_train(model):
     """
     آموزش مدل برای تسک NER
@@ -41,7 +46,7 @@ def main_train(model):
     """
     
     time = datetime.datetime.now()
-    model_title = f"{model}--{time.year}-{time.month}-{time.day}--{time.hour}-{time.minute}-{time.second}".replace('/','--')
+    model_title = f"{time.year}-{digit_correct(time.month)}-{digit_correct(time.day)}--{digit_correct(time.hour)}-{digit_correct(time.minute)}-{digit_correct(time.second)}--{model}".replace('/','--')
     print(f'\nMODEL:: {model}\n')
 
     #!pip install 'flair==0.10'
@@ -54,11 +59,11 @@ def main_train(model):
     #اسم دیتاست اینجا تنظیم شود 
     corpus = ColumnCorpus(data_folder, columns,
                                 #train_file = 'peyma_train.txt')
-                                train_file = 'DATASET140402_no_aref.txt', # qavanin 36K tokens
-                                test_file = 'test_ds_new.txt',) # test 110 sections - 6.7K
+                                train_file = 'DATASET140402_no_aref2.txt', # qavanin 36K tokens
+                                # test_file = 'test_ds_new.txt', # test 110 sections - 6.7K
                                 #dev_file = 'dev split 2.txt'
                                 #max_sentence_length=500
-                                #)
+                                )
 
     # tag to predict
     tag_type = 'ner'
@@ -159,16 +164,18 @@ def main_train(model):
     F1 Score: {result}
     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n'''
 
-    # final_result = f"""Model Name: {model}
-    # Fine-Tune Parameters: {hyperparameters}
-    # {train_result}
-    # {evaluate_result}\n
-    # Fine_Tune time: {operation_time}
-    # ------------------------------------------------------------------------------------
-    # ------------------------------------------------------------------------------------\n
-    # """
-    # save_to_file_by_address('./data/train_log.txt', final_result)
-    # print(' Saving results finished! ')
+    hyperparameters = f"""learning_rate: {learning_rate} - mini_batch_size: {mini_batch_size} - max_epochs: {max_epochs}"""
+
+    final_result = f"""Model Name: {model}
+    Fine-Tune Parameters: {hyperparameters}
+    {train_result}
+    {evaluate_result}\n
+    Fine_Tune time: {operation_time}
+    ------------------------------------------------------------------------------------
+    ------------------------------------------------------------------------------------\n
+    """
+    save_to_file_by_address('./data/train_log.txt', final_result)
+
     return True
 
 models = """
@@ -177,8 +184,11 @@ HooshvareLab/bert-fa-base-uncased-ner-peyma
 HooshvareLab/bert-base-parsbert-armanner-uncased
 HooshvareLab/bert-fa-base-uncased-ner-arman
 HooshvareLab/bert-base-parsbert-peymaner-uncased
-HooshvareLab/distilbert-fa-zwnj-base-ner
 """
+models = """
+HooshvareLab/bert-fa-base-uncased-ner-peyma
+"""
+# HooshvareLab/distilbert-fa-zwnj-base-ner
 models_with_error= """
 nicolauduran45/affilgood-ner-multilingual-v2 - error
 Amirmerfan/bert-base-uncased-persian-ner-50k-base - error