add some log

paddlemix/trainer/benchmark_callback.py

@@ -347,7 +347,7 @@ def on_log(self, args, state, control, logs=None, **kwargs):
         """
         record the infomation of a logging step.
         """
-        if self.benchmark_mode:
+        if self.benchmark_mode and "loss" in logs:
             logs.update(self.state.get_result())
             logs[self.ACC_SAMPLES] = state.trial_params[self.ACC_SAMPLES]
             logs[self.ACC_TOKENS] = state.trial_params[self.ACC_TOKENS]
@@ -373,20 +373,3 @@ def on_log(self, args, state, control, logs=None, **kwargs):
                     max_mem_allocated_msg,
                 )
             )
-
-    def _log(self, logs):
-        """
-        record the information accurately and neatly.
-        """
-        logs_str = []
-        logs_str = []
-        for k, v in logs.items():
-            if isinstance(v, float):
-                if abs(v) < 1e-3:
-                    v = f"{v:e}"
-                elif abs(v) > 100:
-                    v = f"{v:.04f}"
-                else:
-                    v = f"{v:.06f}"
-            logs_str.append(f"{k}: {v}")
-        logger.info(", ".join(logs_str))

paddlemix/trainer/llava_trainer.py

@@ -125,7 +125,7 @@ def __init__(self, **kwargs):
             # self.benchmark_callback = BenchmarkCallback(self, self.args.save_steps, skip_step=self.args.benchmark_skip_steps, self.args.benchmark)
             self.benchmark_callback = BenchmarkCallback(
                 self, 
-                self.args.max_steps if self.args.max_steps>1 else 1000, 
+                self.args.max_steps if self.args.max_steps>1 else 10000, 
                 1, 
                 self.args.benchmark)
             self.add_callback(self.benchmark_callback)