Upload finetune_coding.py with huggingface_hub

finetune_coding.py

@@ -80,8 +80,13 @@ def format_roman(example):
 def format_coderforge(example):
     """
     CoderForge agentic trajectories: messages is a JSON string in OpenHands format.
-    Merges all assistant+tool turns into a single Apertus assistant message with
-    interleaved TOOL_CALLS and TOOL_OUTPUTS blocks.
+    Merges all assistant+tool turns into a single Apertus assistant message.
+
+    Block mapping:
+      assistant with tool_calls  → THOUGHTS (the explanation) + TOOL_CALLS (the action)
+      tool result                → TOOL_OUTPUTS
+      assistant without tool_calls (final) → RESPONSE
+    This ordering is valid in the Apertus format (RESPONSE may not precede TOOL_OUTPUTS).
     """
     try:
         raw = json.loads(example["messages"])
@@ -110,6 +115,11 @@ def format_coderforge(example):
             agentic_started = True
             tool_calls_raw = msg.get("tool_calls") or []
             if tool_calls_raw:
+                # Content alongside tool_calls is the model's reasoning → THOUGHTS
+                if content:
+                    agentic_blocks.append(
+                        AssistantBlock(type=BlockType.THOUGHTS, text=content)
+                    )
                 calls = [
                     ToolCall(
                         name=tc["function"]["name"],
@@ -122,7 +132,8 @@ def format_coderforge(example):
                     agentic_blocks.append(
                         AssistantBlock(type=BlockType.TOOL_CALLS, calls=calls)
                     )
-            if content:
+            elif content:
+                # No tool calls: this is a final text response
                 agentic_blocks.append(
                     AssistantBlock(type=BlockType.RESPONSE, text=content)
                 )
@@ -139,8 +150,6 @@ def format_coderforge(example):
     if not agentic_blocks:
         return {"text": None}
 
-    # If the last block is TOOL_CALLS or TOOL_OUTPUTS (no final text response),
-    # the trajectory is still useful — leave it as-is.
     all_msgs = system_msgs + user_msgs + [Message.assistant_with_blocks(agentic_blocks)]
     try:
         return {"text": formatter.format_conversation(Conversation(messages=all_msgs))}
@@ -221,15 +230,15 @@ config = SFTConfig(
     hub_strategy="every_save",
 
     dataset_text_field="text",
-    max_length=4096,
+    max_length=2048,  # 4096 caused OOM on a10g-large; 2048 fits with room to spare
 
     num_train_epochs=2,
-    per_device_train_batch_size=2,
+    per_device_train_batch_size=1,   # reduced from 2 to avoid OOM
     per_device_eval_batch_size=1,
-    gradient_accumulation_steps=8,
+    gradient_accumulation_steps=16,  # keeps effective batch at 16
     learning_rate=2e-4,
     lr_scheduler_type="cosine",
-    warmup_ratio=0.05,
+    warmup_steps=100,
     bf16=True,
     gradient_checkpointing=True,