INNER CODE UNIT · TypeScript

_log_metrics

theaniketgiri/create-llm · src/python-callback-templates.ts:328

    def _log_metrics(self, trainer: Any, step: int, loss: float, metrics: Optional[dict]):
        """Log metrics to console, file, and TensorBoard"""
        elapsed = time.time() - self.start_time
        
        # Calculate tokens per second
        tokens_per_sec = 0
        if hasattr(trainer, 'tokens_processed'):
            tokens_per_sec = trainer.tokens_processed / elapsed
        
        # Get learning rate
        lr = trainer.optimizer.param_groups[0]['lr']
        
        # Log to file
        log_path = self.log_dir / self.log_file
        with open(log_path, 'a') as f:
            f.write(f"{step},{loss:.6f},{lr:.6e},{tokens_per_sec:.2f},{elapsed:.2f}\\n")
        
        # Log to TensorBoard

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