Try to understand and apply Sylvain's comments (#8458)

examples/token-classification/run_ner.py

@@ -163,6 +163,8 @@ def main():
     # Set the verbosity to info of the Transformers logger (on main process only):
     if is_main_process(training_args.local_rank):
         transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info("Training/evaluation parameters %s", training_args)
 
     # Set seed before initializing model.

examples/token-classification/run_ner_old.py

@@ -25,6 +25,7 @@ import numpy as np
 from seqeval.metrics import accuracy_score, f1_score, precision_score, recall_score
 from torch import nn
 
+import transformers
 from transformers import (
     AutoConfig,
     AutoModelForTokenClassification,
@@ -35,6 +36,7 @@ from transformers import (
     TrainingArguments,
     set_seed,
 )
+from transformers.trainer_utils import is_main_process
 from utils_ner import Split, TokenClassificationDataset, TokenClassificationTask
 
 
@@ -139,6 +141,11 @@ def main():
         bool(training_args.local_rank != -1),
         training_args.fp16,
     )
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(training_args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info("Training/evaluation parameters %s", training_args)
 
     # Set seed

examples/token-classification/run_tf_ner.py

@@ -33,9 +33,15 @@ from transformers import (
     TFTrainer,
     TFTrainingArguments,
 )
+from transformers.utils import logging as hf_logging
 from utils_ner import Split, TFTokenClassificationDataset, TokenClassificationTask
 
 
+hf_logging.set_verbosity_info()
+hf_logging.enable_default_handler()
+hf_logging.enable_explicit_format()
+
+
 logger = logging.getLogger(__name__)