- Implemented target construction in `targets.py` for next-token and unique-time set supervision. - Added validation functions and utility methods for target building. - Created a comprehensive training script in `train.py` that includes data loading, model building, optimizer setup, and training loop with early stopping and logging. - Integrated loss functions and readout mechanisms based on target modes. - Established dataset splitting and DataLoader configurations for training, validation, and testing.
11 KiB
11 KiB