Files
drc-ners-nlp/ner.py
T

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Python
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#!/usr/bin/env python3
import argparse
import logging
import sys
from pathlib import Path
from core.config import setup_config
from processing.ner.ner_data_builder import NERDataBuilder
from processing.ner.ner_name_model import NERNameModel
def train(config_path=None, env="development"):
"""Train the NER model."""
try:
config = setup_config(config_path=config_path, env=env)
trainer = NERNameModel(config)
builder = NERDataBuilder(config)
data_path = Path(config.paths.data_dir) / config.data.output_files["ner_data"]
if not data_path.exists():
builder.build()
trainer.create_blank_model("fr")
data = trainer.load_data(str(data_path))
split_idx = int(len(data) * 0.8)
train_data, eval_data = data[:split_idx], data[split_idx:]
logging.info(f"Training with {len(train_data)} examples, evaluating on {len(eval_data)}")
trainer.train(train_data, epochs=1, batch_size=config.processing.batch_size, dropout_rate=0.3)
trainer.evaluate(eval_data)
model_path = trainer.save()
logging.info(f"Model saved to: {model_path}")
return 0
except Exception as e:
logging.error(f"NER Training failed: {e}", exc_info=True)
return 1
def main():
parser = argparse.ArgumentParser(description="Train NER model for DRC names")
parser.add_argument("--config", type=str, help="Path to configuration file")
parser.add_argument("--env", type=str, default="development", help="Environment name")
args = parser.parse_args()
sys.exit(train(config_path=args.config, env=args.env))
if __name__ == "__main__":
main()