your message here

edited attribution

cleaned up code/print statements/comments

ablation fix

Merge branch 'katherine_branch'

moved error_analysis.png

revised readme/setup/added diagnose leakage back

file organization/deleting redundant files

Merge branch 'main' of https://github.com/sashpol111/burnout-tracker

file organization / deletion

add accurate ATTRIBUTION.md

rewrite comments in data_loader.py and data_pipeline.py

add individual contributions section

update evaluation tables with real preprocessing experiment results

Merge branch 'katherine_branch'

Merge branch 'main' of https://github.com/sashpol111/burnout-tracker

created data pipeline engineering: 3 sources (apis and synthetic data) merged into 1 data set

update README with YAML header and evaluation tables

fixed error analysis

rewrote / fixed error_analysis. generates png of 4 visualizations

fixed ai coach--multi-step ML pipeline that connects multiple models

implemented regularization techniques: l1/l2 & early stopping

fixed deterministic issue + created preprocessing data pipeline

preprocessing

readme

readme & setup fixed

readme + setup

added inference time

DistilBERT fine-tuning complete - F1 0.753 AUC 0.925

synthetic data pipeline - 310 entries generated, F1 improves 0.893 to 0.895

add synthetic data generation, error analysis, train with synthetic pipeline

add error analysis with confusion matrix and failure case analysis

ablation study - 5 feature set experiments documented

fix system_prompt bug in get_burnout_advice

fix colorTo to yellow

add HF Spaces README config

remove pkl files, retrain on startup for HF Spaces

add requirements and app for HF Spaces deployment

initial commit

add Groq LLM advisor with burnout coaching

add visualizations - feature importance, training curves, model comparison

tune XGBoost with regularization - train 0.971 val 0.954

add gitignore

add data pipeline, baseline, and XGBoost model

initial project structure