example script is done

Author: Merlinish

named-entity-recognition/run_ner.py

@@ -246,7 +246,10 @@ def compute_metrics(p: EvalPrediction) -> Dict:
         trainer.save_model()
         # For convenience, we also re-save the tokenizer to the same directory,
         # so that you can share your model easily on huggingface.co/models =)
-        if trainer.is_world_master():
+
+        # error log: Replace "is_world_master" with "is_world_process_zero"
+
+        if trainer.is_world_process_zero():
             tokenizer.save_pretrained(training_args.output_dir)
 
     # Evaluation
@@ -257,7 +260,9 @@ def compute_metrics(p: EvalPrediction) -> Dict:
         result = trainer.evaluate()
 
         output_eval_file = os.path.join(training_args.output_dir, "eval_results.txt")
-        if trainer.is_world_master():
+
+        # error log: Replace "is_world_master" with "is_world_process_zero"
+        if trainer.is_world_process_zero():
             with open(output_eval_file, "w") as writer:
                 logger.info("***** Eval results *****")
                 for key, value in result.items():
@@ -284,7 +289,9 @@ def compute_metrics(p: EvalPrediction) -> Dict:
 
         # Save predictions
         output_test_results_file = os.path.join(training_args.output_dir, "test_results.txt")
-        if trainer.is_world_master():
+
+        # error log: Replace "is_world_master" with "is_world_process_zero"
+        if trainer.is_world_process_zero():
             with open(output_test_results_file, "w") as writer:
                 logger.info("***** Test results *****")
                 for key, value in metrics.items():
@@ -293,7 +300,9 @@ def compute_metrics(p: EvalPrediction) -> Dict:
 
 
         output_test_predictions_file = os.path.join(training_args.output_dir, "test_predictions.txt")
-        if trainer.is_world_master():
+
+        # error log: Replace "is_world_master" with "is_world_process_zero"
+        if trainer.is_world_process_zero():
             with open(output_test_predictions_file, "w") as writer:
                 with open(os.path.join(data_args.data_dir, "test.txt"), "r") as f:
                     example_id = 0