update some parameters in finetuning bert tutorial

Author: x4nth055

machine-learning/nlp/bert-text-classification/finetune-bert.ipynb

@@ -208,8 +208,8 @@
         "    logging_dir='./logs',            # directory for storing logs\n",
         "    load_best_model_at_end=True,     # load the best model when finished training (default metric is loss)\n",
         "    # but you can specify `metric_for_best_model` argument to change to accuracy or other metric\n",
-        "    logging_steps=200,               # log & save weights each logging_steps\n",
-        "    save_steps=200,\n",
+        "    logging_steps=400,               # log & save weights each logging_steps\n",
+        "    save_steps=400,\n",
         "    evaluation_strategy=\"steps\",     # evaluate each `logging_steps`\n",
         ")"
       ]

machine-learning/nlp/bert-text-classification/train.py

@@ -92,8 +92,8 @@ def compute_metrics(pred):
     logging_dir='./logs',            # directory for storing logs
     load_best_model_at_end=True,     # load the best model when finished training (default metric is loss)
     # but you can specify `metric_for_best_model` argument to change to accuracy or other metric
-    logging_steps=200,               # log & save weights each logging_steps
-    save_steps=200,
+    logging_steps=400,               # log & save weights each logging_steps
+    save_steps=400,
     evaluation_strategy="steps",     # evaluate each `logging_steps`
 )