feat: add NER testing interface and evaluation statistics handling
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@@ -44,10 +44,11 @@ def train(config: PipelineConfig):
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batch_size=config.processing.batch_size,
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dropout_rate=0.3,
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)
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name_model.evaluate(eval_data)
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evaluation_results = name_model.evaluate(eval_data)
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model_path = name_model.save()
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logging.info(f"Model saved to: {model_path}")
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print(f"Evaluation results: {evaluation_results}")
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def run_pipeline(config: PipelineConfig, reset: bool = False):
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