small fix

applications/ColossalChat/coati/distributed/grpo_consumer.py

@@ -206,12 +206,6 @@ class GRPOConsumer(BaseConsumer):
         total_samples = all_reduce_sum(torch.sum(torch.ones_like(loss_mask, device=loss_mask.device)), self.plugin)
         self.effective_sample_count += effective_samples.item()
         self.total_sample_count += total_samples.item()
-        print(
-            loss_mask,
-            self.effective_sample_count,
-            self.total_sample_count,
-            self.batch_size * self.dp_size * self.num_generations * 0.75,
-        )
 
         mean_kl, mean_loss = [], []
 
@@ -426,17 +420,19 @@ class GRPOConsumer(BaseConsumer):
                     self.plugin.pp_size > 1 and self.booster.plugin.stage_manager.is_last_stage() and self.tp_rank == 0
                 ):
                     to_log_msg = (
-                        f"Loss: {self.accum_loss.item() / self.accum_count:.4f} \
+                        [
-                        Reward: {self.accum_reward.item() / self.accum_count:.4f} \
+                            f"Loss: {self.accum_loss.item() / self.accum_count:.4f}",
-                        Format Reward: {self.accum_format_acc.item() / self.accum_count:.4f} \
+                            f"Reward: {self.accum_reward.item() / self.accum_count:.4f}",
-                        Acc Reward: {self.accum_ans_acc.item() / self.accum_count:.4f} \
+                            f"ormat Reward: {self.accum_format_acc.item() / self.accum_count:.4f}",
-                        Advantages: {self.accum_advantages.item() / self.accum_count:.4f} \
+                            f"Acc Reward: {self.accum_ans_acc.item() / self.accum_count:.4f}",
-                        Response Length: {self.accum_response_length.item() / self.accum_count:.4f}"
+                            f"Advantages: {self.accum_advantages.item() / self.accum_count:.4f}",
-                        + f" KL: {self.accum_kl.item() / self.accum_count:.4f}"
+                            f"Response Length: {self.accum_response_length.item() / self.accum_count:.4f}",
+                        ]
+                        + [f"KL: {self.accum_kl.item() / self.accum_count:.4f}"]
                         if self.policy_loss_fn.beta > 0
-                        else ""
+                        else []
                     )
-                    print(to_log_msg)
+                    print("\n".join(to_log_msg))
                     metrics = {
                         "metrics/reward": self.accum_reward.item() / self.accum_count,
                         "metrics/format_acc": self.accum_format_acc.item() / self.accum_count,

applications/ColossalChat/coati/distributed/reward/reward_fn.py

@@ -35,9 +35,10 @@ def math_reward_fn(input_ids, gt_answer, response_idx, **kwargs):
         format_acc += 1
         reward += format_score
 
-    # Check answer accuracy
+    # Check answer accuracy, answer is considered correct if the answer is correct and the format is valid
     if (
-        final_answer is not None
+        format_valid
+        and final_answer is not None
         and gt_answer.strip().replace(" ", "").lower() == final_answer.strip().replace(" ", "").lower()
     ):
         ans_acc += 1