Today I felt stuck and didn’t do anything new.


Today I reviewed my model's predictions and logged the results.


Today I let myself stay unproductive the entire session.


Today I looked at model metrics and compared loss values.


Today I co-led a group session on dataset building techniques.


Today I confirmed that my label categories are evenly distributed.


Today I created examples that clearly differentiate each label category.


Today I polished the documentation and added usage notes for the dataset.


Today I realized I didn’t save my work from the last session and didn’t restart.


Today I failed to follow through on my commitment.


Today I added automated feedback to my model evaluation output.


Today I closed the notebook without making any edits.


Today I updated my training script to include detailed logging.


Today I didn’t have the energy to focus on the project.


Today I assisted with debugging a teammate’s Colab notebook.


Today I made a few updates to the training configuration.


Today I helped another intern understand the differences between label levels.


Today I planned a few things but executed none of them.


Today I avoided working on my task because it felt overwhelming.


Today I compared my current model to one from a few days ago.


Today I tested my model on new data and got typical results.


Today I wrote a function to print check-in predictions cleanly.


Today I evaluated model performance using a new set of check-ins.


Today I felt lost and didn’t take action.


Today I split my dataset into training and validation sets.


Today I added guidance for new labelers based on what I learned.


Today I converted old check-in logs into new training examples.


Today I helped resolve a file structure error in a shared project.


Today I opened my Colab notebook but didn’t run any cells.


Today I created a batch evaluation script for all check-in types.


Today I double-checked the structure of my JSONL entries.


Today I gave feedback on a peer’s model output.


Today I formatted my check-ins using consistent sentence structure.


Today I used a pipeline to evaluate new examples.


Today I had a window to work but didn’t use it.


Today I finished building a prediction review interface in Colab.


Today I tested prediction quality using sample Slack messages.


Today I reviewed and corrected several borderline check-ins for better accuracy.


Today I rewrote outdated examples to better reflect label guidelines.


Today I used past check-in data to inform how I trained the next version.


Today I only opened my files and didn’t do anything else.


Today I created placeholder text for missing check-in examples.


Today I helped compare results from the last two model checkpoints.


Today I contributed zero effort to the task.


Today I helped clean up some spacing and label errors in my data.


Today I helped clarify confusion about what qualifies as ‘above average’.


Today I didn’t get around to opening any project files.


Today I did not contribute to the model or the dataset.