Concise monthly summary for 2025-09 focusing on business value and technical achievements for lab-cosmo/atomistic-cookbook. Key features delivered: - Pet Finetuning Configuration Tuning: Tuned hyperparameters to improve efficiency under resource constraints. Adjusted batch size and reduced epochs across finetuning options to shorten training times and manage memory usage. Commits: b45bae92423dd8efe7393d81cff1152029dd5c5c; 04912323a92cd7c11cfcb8752a3a678c6ea11ba3. - Pet Finetuning Checkpoint Load Utility Refactor: Refactored finetuning script to load models from checkpoints using a new utility function (model_to_checkpoint) to improve robustness and code organization. Commit: f08fa1e7fb6108ff196503c9c040b3cfd1167915. Major bugs fixed: - No major bugs reported for this period in this repository. Maintenance focused on robustness of finetuning workflows and memory-conscious configurations. Overall impact and accomplishments: - Enabled faster experimentation and model customization under constrained compute, reducing time-to-value for pet finetuning tasks. - Improved stability and maintainability of the finetuning pipeline through a dedicated checkpoint-loading utility and clearer config variants. - Improved resource efficiency (lower memory footprint) and predictable training times, aiding reproducibility and scaling. Technologies/skills demonstrated: - Python scripting and orchestration for ML workflows - Hyperparameter tuning and resource management (batch size, epoch counts) - Code refactoring and modularization (checkpoint loading utility) - Version-controlled changes with clear commits for reproducibility and auditability

July 2025 monthly summary for lab-cosmo/pet-mad focused on stabilizing PETMADFeaturizer versioning to balance access to ongoing improvements with predictable, reproducible behavior. Implemented a versioning strategy that initially uses the latest stable version via LATEST_VERSION and get_pet_mad, then reverted to a default 'latest' string to simplify maintenance and ensure stability. This approach reduces upgrade risk while keeping a pathway for future updates.

June 2025 performance summary for lab-cosmo/pet-mad focused on targeted improvements to correctness, readability, and user-facing documentation. Delivered explicit keyword-argument refactor, clarified version support in PETMADCalculator docs, and completed a code-quality cleanup to improve long-term maintainability.