Upload main.py

main.py

@@ -10,7 +10,29 @@
 #     "mpi4py"
 # ]
 # ///
+import time
+from transformers import TrainerCallback
 
+class SpeedCallback(TrainerCallback):
+    def __init__(self):
+        self.last_time = None
+
+    def on_step_begin(self, args, state, control, **kwargs):
+        self.last_time = time.time()
+
+    def on_step_end(self, args, state, control, **kwargs):
+        if self.last_time is None:
+            return
+
+        elapsed = time.time() - self.last_time
+        remaining = max(0, state.max_steps - state.global_step)
+        eta_min = remaining * elapsed / 60
+
+        print(
+            f"[speed] step {state.global_step}/{state.max_steps} | "
+            f"{elapsed:.2f}s/step | ETA {eta_min:.1f} min",
+            flush=True,
+        )
 import inspect
 
 import datasets
@@ -23,7 +45,7 @@ from transformers import AutoTokenizer
 # -----------------------------
 
 STUDENT_MODEL = "Qwen/Qwen2.5-0.5B-Instruct"
-TEACHER_MODEL = "Qwen/Qwen2.5-Coder-7B-Instruct"
+TEACHER_MODEL = "Qwen/Qwen2.5-Coder-1.5B-Instruct"
 
 OUTPUT_DIR = "gold-code-deepspeed-test"
 
@@ -35,10 +57,6 @@ OUTPUT_DIR = "gold-code-deepspeed-test"
 DS_CONFIG = {
      "zero_optimization": {
          "stage": 2,
-         "offload_optimizer": {
-             "device": "cpu",
-             "pin_memory": True,
-         },
          "overlap_comm": True,
          "contiguous_gradients": True,
      },
@@ -101,7 +119,7 @@ def main():
     print("Loading dataset...")
     raw = datasets.load_dataset(
         "deepmind/code_contests",
-        split="train[:100]",
+        split="train[:10000]",
     )
 
     print("Raw columns:", raw.column_names)
@@ -121,9 +139,10 @@ def main():
         temperature=0.8,
         top_p=0.95,
         max_length=1024,
-
+        disable_tqdm=True,
+        logging_steps=1,
         # Training settings
-        max_steps=24,
+        max_steps=2000,
         per_device_train_batch_size=1,
         gradient_accumulation_steps=4,
         learning_rate=5e-6,
@@ -135,7 +154,8 @@ def main():
 
         # Precision
         bf16=True,
-
+        hub_model_id="moos124/gold-code-deepspeed-testV2",
+        push_to_hub=True,
         # DeepSpeed
         deepspeed=DS_CONFIG,
     )
@@ -159,15 +179,14 @@ def main():
 
     print("Building GOLDTrainer...")
     trainer = gold.GOLDTrainer(**trainer_kwargs)
-
+    trainer.add_callback(SpeedCallback())
     print("Training...")
     trainer.train()
 
     print("Saving...")
     trainer.save_model(OUTPUT_DIR)
-
     # Optional push
-    trainer.push_to_hub("moos124/gold-code-deepspeed-test")
+    trainer.push_to_hub()
 
 
 if __name__ == "__main__":