azure / azure-llm-fine-tuning
File Change Frequency

File change frequency (churn) shows the distribution of file updates (days with at least one commit).

Overview
File Change Frequency Overall
  • There are 22 files with 5,703 lines of code.
    • 0 files changed more than 100 times (0 lines of code)
    • 0 files changed 51-100 times (0 lines of code)
    • 0 files changed 21-50 times (0 lines of code)
    • 0 files changed 6-20 times (0 lines of code)
    • 22 files changed 1-5 times (5,703 lines of code)
0% | 0% | 0% | 0% | 100%
Legend:
101+
51-100
21-50
6-20
1-5

explore: grouped by folders | grouped by update frequency | data
Contributors Count Frequency Overall
  • There are 22 files with 5,703 lines of code.
    • 0 files changed by more than 25 contributors (0 lines of code)
    • 0 files changed by 11-25 contributors (0 lines of code)
    • 0 files changed by 6-10 contributors (0 lines of code)
    • 0 files changed by 2-5 contributors (0 lines of code)
    • 22 files changed by 1 contributor (5,703 lines of code)
0% | 0% | 0% | 0% | 100%
Legend:
26+
11-25
6-10
2-5
1

explore: grouped by folders | grouped by contributors count | data
File Change Frequency per File Extension
py, json, ipynb, txt, md, yaml, jsonl, gitignore, prettierignore
File Change Frequency per Extension
The number of recorded file updates
101+
51-100
21-50
6-20
1-5
ipynb0% | 0% | 0% | 0% | 100%
py0% | 0% | 0% | 0% | 100%
yaml0% | 0% | 0% | 0% | 100%
jsonl0% | 0% | 0% | 0% | 100%
File Change Frequency per Logical Decomposition
primary
primary (file change frequency)
The number of recorded file updates
101+
51-100
21-50
6-20
1-5
phi30% | 0% | 0% | 0% | 100%
florence2-VQA0% | 0% | 0% | 0% | 100%
aoai0% | 0% | 0% | 0% | 100%
Most Frequently Changed Files (Top 22)

See data for all files...

File# lines# unitscreatedlast modified# changes
(days)		# contributorsfirst
contributor		latest
contributor
score.py
in phi3/src_serve
 28 2 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
train_tokenizer.py
in phi3/dataset-preparation
 51 2 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
1_data-preparation-basic.ipynb
in phi3/dataset-preparation
 189 - 2024-06-30 2024-11-04 3 1 housekdk@naver.com housekdk@naver.com
train.py
in phi3/src_train
 204 4 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
train_mlflow.py
in phi3/src_train
 208 5 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
logger.py
in florence2-VQA
 12 - 2024-09-30 2024-11-04 2 1 housekdk@naver.com housekdk@naver.com
combine_tokenizer.py
in phi3/dataset-preparation
 39 2 2024-06-30 2024-09-05 2 1 housekdk@naver.com housekdk@naver.com
score.py
in florence2-VQA/src_serve
 57 3 2024-06-30 2024-11-04 2 1 housekdk@naver.com housekdk@naver.com
572 - 2024-11-04 2025-03-17 2 1 housekdk@naver.com housekdk@naver.com
jsonl
validation_set.jsonl
in aoai/dataset
 10 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
jsonl
training_set.jsonl
in aoai/dataset
 10 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
logger.py
in phi3
 12 - 2024-09-05 2024-09-05 1 1 housekdk@naver.com housekdk@naver.com
logger.py
in aoai
 12 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
conda.yaml
in phi3/olive
 25 - 2024-11-04 2024-11-04 1 1 housekdk@naver.com housekdk@naver.com
train_mlflow.py
in florence2-VQA/src_train
 206 10 2024-06-30 2024-06-30 1 1 housekdk@naver.com housekdk@naver.com
244 12 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
phi3.py
in phi3/olive
 260 5 2024-11-04 2024-11-04 1 1 housekdk@naver.com housekdk@naver.com
384 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
640 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
811 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
863 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
866 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
Files With Most Contributors (Top 22)
Based on the number of unique email addresses found in commits.

See data for all files...

File# lines# unitscreatedlast modified# changes
(days)		# contributorsfirst
contributor		latest
contributor
train.py
in phi3/src_train
 204 4 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
train_mlflow.py
in phi3/src_train
 208 5 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
train_tokenizer.py
in phi3/dataset-preparation
 51 2 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
1_data-preparation-basic.ipynb
in phi3/dataset-preparation
 189 - 2024-06-30 2024-11-04 3 1 housekdk@naver.com housekdk@naver.com
score.py
in phi3/src_serve
 28 2 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
572 - 2024-11-04 2025-03-17 2 1 housekdk@naver.com housekdk@naver.com
combine_tokenizer.py
in phi3/dataset-preparation
 39 2 2024-06-30 2024-09-05 2 1 housekdk@naver.com housekdk@naver.com
score.py
in florence2-VQA/src_serve
 57 3 2024-06-30 2024-11-04 2 1 housekdk@naver.com housekdk@naver.com
logger.py
in florence2-VQA
 12 - 2024-09-30 2024-11-04 2 1 housekdk@naver.com housekdk@naver.com
244 12 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
jsonl
training_set.jsonl
in aoai/dataset
 10 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
jsonl
validation_set.jsonl
in aoai/dataset
 10 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
384 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
logger.py
in aoai
 12 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
866 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
phi3.py
in phi3/olive
 260 5 2024-11-04 2024-11-04 1 1 housekdk@naver.com housekdk@naver.com
conda.yaml
in phi3/olive
 25 - 2024-11-04 2024-11-04 1 1 housekdk@naver.com housekdk@naver.com
863 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
logger.py
in phi3
 12 - 2024-09-05 2024-09-05 1 1 housekdk@naver.com housekdk@naver.com
train_mlflow.py
in florence2-VQA/src_train
 206 10 2024-06-30 2024-06-30 1 1 housekdk@naver.com housekdk@naver.com
811 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
640 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
Files With Least Contributors (Top 22)
Based on the number of unique email addresses found in commits.

See data for all files...

File# lines# unitscreatedlast modified# changes
(days)		# contributorsfirst
contributor		latest
contributor
866 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
863 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
811 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
640 - 2025-03-17 2025-03-17 1 1 housekdk@naver.com housekdk@naver.com
572 - 2024-11-04 2025-03-17 2 1 housekdk@naver.com housekdk@naver.com
384 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
phi3.py
in phi3/olive
 260 5 2024-11-04 2024-11-04 1 1 housekdk@naver.com housekdk@naver.com
244 12 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
train_mlflow.py
in phi3/src_train
 208 5 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
train_mlflow.py
in florence2-VQA/src_train
 206 10 2024-06-30 2024-06-30 1 1 housekdk@naver.com housekdk@naver.com
train.py
in phi3/src_train
 204 4 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
1_data-preparation-basic.ipynb
in phi3/dataset-preparation
 189 - 2024-06-30 2024-11-04 3 1 housekdk@naver.com housekdk@naver.com
score.py
in florence2-VQA/src_serve
 57 3 2024-06-30 2024-11-04 2 1 housekdk@naver.com housekdk@naver.com
train_tokenizer.py
in phi3/dataset-preparation
 51 2 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
combine_tokenizer.py
in phi3/dataset-preparation
 39 2 2024-06-30 2024-09-05 2 1 housekdk@naver.com housekdk@naver.com
score.py
in phi3/src_serve
 28 2 2024-06-30 2025-03-17 3 1 housekdk@naver.com housekdk@naver.com
conda.yaml
in phi3/olive
 25 - 2024-11-04 2024-11-04 1 1 housekdk@naver.com housekdk@naver.com
logger.py
in aoai
 12 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
logger.py
in phi3
 12 - 2024-09-05 2024-09-05 1 1 housekdk@naver.com housekdk@naver.com
logger.py
in florence2-VQA
 12 - 2024-09-30 2024-11-04 2 1 housekdk@naver.com housekdk@naver.com
jsonl
training_set.jsonl
in aoai/dataset
 10 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
jsonl
validation_set.jsonl
in aoai/dataset
 10 - 2024-09-30 2024-09-30 1 1 housekdk@naver.com housekdk@naver.com
Correlations

File Size vs. Number of Changes: 22 points

florence2-VQA/1_training_mlflow_florence2.ipynb x: 640 lines of code y: 1 # changes florence2-VQA/2_serving_florence2.ipynb x: 811 lines of code y: 1 # changes phi3/1_training_custom_phi3.ipynb x: 863 lines of code y: 1 # changes phi3/1_training_mlflow_phi3.ipynb x: 866 lines of code y: 1 # changes phi3/src_serve/score.py x: 28 lines of code y: 3 # changes phi3/src_train/train.py x: 204 lines of code y: 3 # changes phi3/src_train/train_mlflow.py x: 208 lines of code y: 3 # changes phi3/3_optimization_olive.ipynb x: 572 lines of code y: 2 # changes phi3/dataset-preparation/train_tokenizer.py x: 51 lines of code y: 3 # changes florence2-VQA/logger.py x: 12 lines of code y: 2 # changes florence2-VQA/src_serve/score.py x: 57 lines of code y: 2 # changes phi3/dataset-preparation/1_data-preparation-basic.ipynb x: 189 lines of code y: 3 # changes phi3/olive/conda.yaml x: 25 lines of code y: 1 # changes phi3/olive/phi3.py x: 260 lines of code y: 1 # changes aoai/aoai_finetune.ipynb x: 384 lines of code y: 1 # changes aoai/dataset/training_set.jsonl x: 10 lines of code y: 1 # changes aoai/logger.py x: 12 lines of code y: 1 # changes aoai/token_count_utils.py x: 244 lines of code y: 1 # changes phi3/dataset-preparation/combine_tokenizer.py x: 39 lines of code y: 2 # changes florence2-VQA/src_train/train_mlflow.py x: 206 lines of code y: 1 # changes
3.0
# changes
  min: 1.0
  average: 1.64
  25th percentile: 1.0
  median: 1.0
  75th percentile: 2.25
  max: 3.0
0 866.0
lines of code
min: 10.0 | average: 259.23 | 25th percentile: 21.75 | median: 196.5 | 75th percentile: 431.0 | max: 866.0

Number of Contributors vs. Number of Changes: 22 points

florence2-VQA/1_training_mlflow_florence2.ipynb x: 1 # contributors y: 1 # changes phi3/src_serve/score.py x: 1 # contributors y: 3 # changes phi3/3_optimization_olive.ipynb x: 1 # contributors y: 2 # changes
3.0
# changes
  min: 1.0
  average: 1.64
  25th percentile: 1.0
  median: 1.0
  75th percentile: 2.25
  max: 3.0
0 1.0
# contributors
min: 1.0 | average: 1.0 | 25th percentile: 1.0 | median: 1.0 | 75th percentile: 1.0 | max: 1.0

Number of Contributors vs. File Size: 22 points

florence2-VQA/1_training_mlflow_florence2.ipynb x: 1 # contributors y: 640 lines of code florence2-VQA/2_serving_florence2.ipynb x: 1 # contributors y: 811 lines of code phi3/1_training_custom_phi3.ipynb x: 1 # contributors y: 863 lines of code phi3/src_serve/score.py x: 1 # contributors y: 28 lines of code phi3/src_train/train.py x: 1 # contributors y: 204 lines of code phi3/src_train/train_mlflow.py x: 1 # contributors y: 208 lines of code phi3/3_optimization_olive.ipynb x: 1 # contributors y: 572 lines of code phi3/dataset-preparation/train_tokenizer.py x: 1 # contributors y: 51 lines of code florence2-VQA/logger.py x: 1 # contributors y: 12 lines of code florence2-VQA/src_serve/score.py x: 1 # contributors y: 57 lines of code phi3/dataset-preparation/1_data-preparation-basic.ipynb x: 1 # contributors y: 189 lines of code phi3/olive/conda.yaml x: 1 # contributors y: 25 lines of code phi3/olive/phi3.py x: 1 # contributors y: 260 lines of code aoai/aoai_finetune.ipynb x: 1 # contributors y: 384 lines of code aoai/dataset/training_set.jsonl x: 1 # contributors y: 10 lines of code aoai/token_count_utils.py x: 1 # contributors y: 244 lines of code phi3/dataset-preparation/combine_tokenizer.py x: 1 # contributors y: 39 lines of code florence2-VQA/src_train/train_mlflow.py x: 1 # contributors y: 206 lines of code
866.0
lines of code
  min: 10.0
  average: 259.23
  25th percentile: 21.75
  median: 196.5
  75th percentile: 431.0
  max: 866.0
0 1.0
# contributors
min: 1.0 | average: 1.0 | 25th percentile: 1.0 | median: 1.0 | 75th percentile: 1.0 | max: 1.0