Upload run_cloud_training.py with huggingface_hub

run_cloud_training.py

@@ -568,8 +568,8 @@ def train(config_path, dataset_name, output_dir, upload_to_hub=False, hub_repo_n
             bf16 = torch.cuda.is_available() and hardware_config.get("bf16", False)
             gradient_checkpointing = torch.cuda.is_available() and hardware_config.get("gradient_checkpointing", True)
             dataloader_workers = training_config.get("dataloader_num_workers", 4)
-            eval_strategy = training_config.get("eval_strategy", "steps")  # Updated from evaluation_strategy
-            load_best_model_at_end = training_config.get("load_best_model_at_end", True)
+            eval_strategy = training_config.get("eval_strategy", "no")  # Changed from "steps" to "no" since we don't have an eval_dataset
+            load_best_model_at_end = False  # Must be False when eval_strategy is "no"
             logger.info("Using full training parameters for GPU mode")
         else:
             # For Space CPU training mode, use minimal parameters