Update trainer configuration in train.py to align evaluation strategy with save strategy. Set eval_steps to match save_steps for consistent evaluation frequency.

Refactor trainer configuration in train.py for improved clarity. Clean up comments and ensure consistent formatting in evaluation strategy and model selection parameters.

Refactor train.py to improve code readability and organization. Adjust logging setup for clarity, streamline dependency installation commands, and enhance dataset splitting and formatting processes. Ensure consistent formatting in log messages and code structure.

Enhance training script for SmolLM2-135M model by adding logging functionality, improving error handling, and implementing dataset validation split. Refactor model loading and dataset preparation processes for better clarity and robustness. Update trainer configuration to include evaluation strategy and logging of final metrics.

Add training script for SmolLM2-135M model using Unsloth. Includes model loading, dataset preparation, and training configuration. Provides detailed instructions for setup and execution.