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burnout-tracker

Commit History

Apr 26

18:51
your message here

sashpol

ac1e7a7
17:44
edited attribution

Katherine

794b100
07:23
cleaned up code/print statements/comments

Katherine

e703447
07:00
ablation fix

Katherine

58e5588
06:54
Merge branch 'katherine_branch'

Katherine

ac5cc9d
06:46
moved error_analysis.png

Katherine

c0fd879
06:42
revised readme/setup/added diagnose leakage back

Katherine

04f77e4
05:55
file organization/deleting redundant files

Katherine

cfaa360
03:04
Merge branch 'main' of https://github.com/sashpol111/burnout-tracker

Katherine

17ef969
02:59
file organization / deletion

Katherine

e3188b7
02:15
add accurate ATTRIBUTION.md

sashpol

dca8254
02:09
rewrite comments in data_loader.py and data_pipeline.py

sashpol

fd99b8f
01:36
add individual contributions section

sashpol

46c498d
01:27
update evaluation tables with real preprocessing experiment results

sashpol

6b434d7
01:11
Merge branch 'katherine_branch'

Katherine

d6bb8d2
01:10
Merge branch 'main' of https://github.com/sashpol111/burnout-tracker

Katherine

98404ca
01:09
created data pipeline engineering: 3 sources (apis and synthetic data) merged into 1 data set

Katherine

3239ea2
00:35
update README with YAML header and evaluation tables

sashpol

d5805a9

Apr 25

22:28
fixed error analysis

Katherine

05977bf
22:28
rewrote / fixed error_analysis. generates png of 4 visualizations

Katherine

8799217
21:54
fixed ai coach--multi-step ML pipeline that connects multiple models

Katherine

04fe416
21:34
implemented regularization techniques: l1/l2 & early stopping

Katherine

9b132e1
21:15
fixed deterministic issue + created preprocessing data pipeline

Katherine

4e48d40
12:00
preprocessing

Katherine

003c0b8
11:29
readme

Katherine

9b287df
11:17
readme & setup fixed

Katherine

bde51d0
11:04
readme + setup

Katherine

bff95b6
10:43
added inference time

Katherine

2c34fd2

Apr 24

17:28
DistilBERT fine-tuning complete - F1 0.753 AUC 0.925

sashpol

0753fe5
17:17
synthetic data pipeline - 310 entries generated, F1 improves 0.893 to 0.895

sashpol

b025afa
13:45
add synthetic data generation, error analysis, train with synthetic pipeline

sashpol

be84f42
13:23
add error analysis with confusion matrix and failure case analysis

sashpol

1ed515e
13:21
ablation study - 5 feature set experiments documented

sashpol

4f56e6d
02:28
fix system_prompt bug in get_burnout_advice

sashpol

768b66b
02:22
fix colorTo to yellow

sashpol

e855665
02:21
add HF Spaces README config

sashpol

326a7c7
02:19
remove pkl files, retrain on startup for HF Spaces

sashpol

7a51c9c
02:11
add requirements and app for HF Spaces deployment

sashpol

baadd65
02:01
initial commit

sashpol

a14b971
01:30
add Groq LLM advisor with burnout coaching

sashpol

c6e3694
01:18
add visualizations - feature importance, training curves, model comparison

sashpol

12275db
01:13
tune XGBoost with regularization - train 0.971 val 0.954

sashpol

667d4b2
01:10
add gitignore

sashpol

0aba2ff
01:10
add data pipeline, baseline, and XGBoost model

sashpol

c97e168
00:37
initial project structure

sashpol

0d89491

Commit History

Apr 26

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

Apr 25

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

Apr 24

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