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dvc.yaml
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dvc.yaml
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stages:
data_collection:
cmd: >
papermill
nbs/01_data_collection.ipynb
scripts/01_data_collection.ipynb
--cwd nbs/
deps:
- nbs/01_data_collection.ipynb
- pdm.lock
- pyproject.toml
- data/raw-data
- .pdm.toml
outs:
- scripts/01_data_collection.ipynb
- data/Concatenated_Orig_data.csv
data_cleaning:
cmd: >
papermill
nbs/02_data_cleaning.ipynb
scripts/02_data_cleaning.ipynb
--cwd nbs/
deps:
- nbs/02_data_cleaning.ipynb
- pdm.lock
- pyproject.toml
- data/Concatenated_Orig_data.csv
- .pdm.toml
outs:
- scripts/02_data_cleaning.ipynb
- data/Concatenated_Clean_data.csv
feature_extraction:
cmd: >
papermill
nbs/03_feature_extraction.ipynb
scripts/03_feature_extraction.ipynb
--cwd nbs/
deps:
- nbs/03_feature_extraction.ipynb
- pdm.lock
- pyproject.toml
- data/Concatenated_Clean_data.csv
- .pdm.toml
outs:
- scripts/03_feature_extraction.ipynb
- data/splits
training:
cmd: >
papermill
nbs/05_training.ipynb
scripts/05_training.ipynb
-p TOKENIZER ${tokenizer}
-p LEARNING_RATE ${learning_rate}
-p BATCH_SIZE ${batch_size}
-p EPOCHS ${epochs}
-p KFOLD ${kfold}
--cwd nbs/
deps:
- nbs/05_training.ipynb
- data/splits/train/FAA-${kfold}.csv
- data/splits/test/FAA-${kfold}.csv
- data/splits/val/FAA-${kfold}.csv
- pdm.lock
- pyproject.toml
- .pdm.toml
outs:
- model/
- scripts/05_training.ipynb
eval:
cmd: >
papermill
nbs/06_inference.ipynb
scripts/06_inference.ipynb
-p KFOLD ${kfold}
--cwd nbs/
deps:
- nbs/06_inference.ipynb
- pdm.lock
- pyproject.toml
- .pdm.toml
- data/splits/val/FAA-${kfold}.csv
outs:
- scripts/06_inference.ipynb
- eval/plots/sklearn:
persist: true
metrics:
- eval/metrics.json:
persist: true
cache: true
plots:
- Confusion matrix:
template: confusion
x: actual
y:
eval/plots/sklearn/confusion_matrix.json: predicted