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feat: add more baseline expirements

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bernard-ng
2025-09-21 00:06:01 +02:00
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README.md
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@@ -65,7 +65,7 @@ stages:
python main.py --env development
```
## NER Processing
## NER Processing (Optional)
This project implements a custom named entity recognition (NER) pipeline tailored for Congolese names.
Its main objective is to accurately identify and tag the different components of a Congolese name,
@@ -75,7 +75,7 @@ specifically distinguishing between the native part and the surname.
python ner.py --env development
```
Once you've built and train the NER model you can use it to annotate **CoMPOSE** name in the original dataset
Once you've built and train the NER model you can use it to annotate **COMPOSE** name in the original dataset
**Running the Pipeline with NER Annotation**
```yaml
@@ -104,20 +104,55 @@ you can define model features, training parameters, and evaluation metrics in th
**Running Experiments**
```bash
# bigru
python train.py --name="bigru" --type="baseline" --env="development"
python train.py --name="cnn" --type="baseline" --env="development"
python train.py --name="lightgbm" --type="baseline" --env="development"
python train.py --name="bigru_native" --type="baseline" --env="development"
python train.py --name="bigru_surname" --type="baseline" --env="development"
python train.py --name="logistic_regression_fullname" --type="baseline" --env="development"
# cnn
python train.py --name="cnn" --type="baseline" --env="development"
python train.py --name="cnn_native" --type="baseline" --env="development"
python train.py --name="cnn_surname" --type="baseline" --env="development"
# lightgbm
python train.py --name="lightgbm" --type="baseline" --env="development"
python train.py --name="lightgbm_native" --type="baseline" --env="development"
python train.py --name="lightgbm_surname" --type="baseline" --env="development"
# logistic regression
python train.py --name="logistic_regression" --type="baseline" --env="development"
python train.py --name="logistic_regression_native" --type="baseline" --env="development"
python train.py --name="logistic_regression_surname" --type="baseline" --env="development"
# lstm
python train.py --name="lstm" --type="baseline" --env="development"
python train.py --name="lstm_native" --type="baseline" --env="development"
python train.py --name="lstm_surname" --type="baseline" --env="development"
# random forest
python train.py --name="random_forest" --type="baseline" --env="development"
python train.py --name="random_forest_native" --type="baseline" --env="development"
python train.py --name="random_forest_surname" --type="baseline" --env="development"
# svm
python train.py --name="svm" --type="baseline" --env="development"
python train.py --name="svm_native" --type="baseline" --env="development"
python train.py --name="svm_surname" --type="baseline" --env="development"
# naive bayes
python train.py --name="naive_bayes" --type="baseline" --env="development"
python train.py --name="naive_bayes_native" --type="baseline" --env="development"
python train.py --name="naive_bayes_surname" --type="baseline" --env="development"
# transformer
python train.py --name="transformer" --type="baseline" --env="development"
python train.py --name="transformer_native" --type="baseline" --env="development"
python train.py --name="transformer_surname" --type="baseline" --env="development"
# xgboost
python train.py --name="xgboost" --type="baseline" --env="development"
python train.py --name="xgboost_native" --type="baseline" --env="development"
python train.py --name="xgboost_surname" --type="baseline" --env="development"
```
## Web Interface