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combined experiment tracking with model training
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31 changes: 0 additions & 31 deletions
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src/swahiliNewsClassifier/pipeline/stage_02_model_training.py
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src/swahiliNewsClassifier/pipeline/stage_02_model_training_and_evaluation.py
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from swahiliNewsClassifier.configuration.configuration import ConfigurationManager | ||
from swahiliNewsClassifier.components.model_training_and_evaluation import ModelTrainingAndEvaluation | ||
from swahiliNewsClassifier import log | ||
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STAGE_NAME = "Model Training and Evaluation Stage" | ||
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class ModelTrainingAndEvaluationPipeline: | ||
def __init__(self): | ||
""" | ||
Initialize the ModelTrainingAndEvaluationPipeline object. | ||
""" | ||
self.config = ConfigurationManager() | ||
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def main(self): | ||
""" | ||
Execute the model training and evaluation process. | ||
""" | ||
try: | ||
model_training_and_evaluation_config = self.config.get_model_training_and_evaluation_config() | ||
model_training_and_evaluation = ModelTrainingAndEvaluation( | ||
model_training_and_evaluation_config=model_training_and_evaluation_config) | ||
model_training_and_evaluation.run_pipeline() | ||
except Exception as e: | ||
log.exception(f"An error occurred during {STAGE_NAME}: {e}") | ||
raise e | ||
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if __name__ == '__main__': | ||
pipeline = ModelTrainingAndEvaluationPipeline() | ||
pipeline.main() |
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