Training Configuration

Model Training Pipeline

The training pipeline is fully automated and triggered by: - Push to main branch - Manual workflow dispatch - Scheduled training jobs

Configuration Options

training:
  batch_size: 32
  learning_rate: 2e-5
  epochs: 10
  max_length: 512
  warmup_steps: 500
  weight_decay: 0.01

evaluation:
  benchmark: GAIA
  levels: [1, 2, 3]
  metrics:
    - accuracy
    - f1_score
    - completion_rate

checkpoints:
  save_strategy: steps
  save_steps: 500
  save_total_limit: 3

Automated Release Process

1. Training completion triggers evaluation
2. Results compared against previous SOTA
3. If improvements detected:
4. New model version tagged
5. Documentation updated
6. Release created
7. Model pushed to Hugging Face Hub

TODO

• [ ] Add dynamic learning rate scheduling
• [ ] Implement multi-GPU training support
• [ ] Add cross-validation pipeline
• [ ] Enhance checkpoint management
• [ ] Implement A/B testing framework