Add text support to the Trainer's TensorBoard integration

src/transformers/integrations/integration_utils.py

@@ -697,6 +697,8 @@ def on_log(self, args, state, control, logs=None, **kwargs):
             for k, v in logs.items():
                 if isinstance(v, (int, float)):
                     self.tb_writer.add_scalar(k, v, state.global_step)
+                elif isinstance(v, str):
+                    self.tb_writer.add_text(k, v, state.global_step)
                 else:
                     logger.warning(
                         "Trainer is attempting to log a value of "

src/transformers/trainer_callback.py

@@ -594,6 +594,7 @@ class ProgressCallback(TrainerCallback):
     def __init__(self):
         self.training_bar = None
         self.prediction_bar = None
+        self.max_str_len = 100
 
     def on_train_begin(self, args, state, control, **kwargs):
         if state.is_world_process_zero:
@@ -631,7 +632,10 @@ def on_log(self, args, state, control, logs=None, **kwargs):
             # but avoid doing any value pickling.
             shallow_logs = {}
             for k, v in logs.items():
-                shallow_logs[k] = v
+                if isinstance(v, str) and len(v) > self.max_str_len:
+                    shallow_logs[k] = f"[String too long to display, length: {len(v)}]"
+                else:
+                    shallow_logs[k] = v
             _ = shallow_logs.pop("total_flos", None)
             # round numbers so that it looks better in console
             if "epoch" in shallow_logs: