fix: correct top_k=0 truthiness check and deduplicate loss_history entries

- Use `is not None` instead of truthiness check for top_k so that
  top_k=0 is passed through correctly instead of being replaced with -1
- Skip appending to loss_history at epoch end when the last step was
  already logged by per-step logging, preventing duplicate entries

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: madiator

src/bespokelabs/curator/finetune/trainer/tinker_trainer.py

@@ -339,7 +339,9 @@ def train(self, dataset: Any) -> TrainingResult:
 
                 if epoch_steps > 0:
                     avg_epoch_loss = epoch_loss / epoch_steps
-                    loss_history.append(avg_epoch_loss)
+                    # Only append if the last step wasn't already logged by per-step logging
+                    if current_step % self.config.log_every_n_steps != 0:
+                        loss_history.append(avg_epoch_loss)
                     logger.info(f"Epoch {epoch}/{self.config.epochs} complete. Average loss: {avg_epoch_loss:.4f}")
                 else:
                     avg_epoch_loss = 0.0
@@ -597,7 +599,7 @@ def sample(
                     max_tokens=sampling_config.max_tokens,
                     temperature=sampling_config.temperature,
                     top_p=sampling_config.top_p,
-                    top_k=sampling_config.top_k if sampling_config.top_k else -1,
+                    top_k=sampling_config.top_k if sampling_config.top_k is not None else -1,
                     stop=sampling_config.stop_sequences if sampling_config.stop_sequences else None,
                 )
                 sample_result = sampling_client.sample(prompt_input, num_samples=1, sampling_params=sample_params).result()