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Bf16 only
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-8
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olmocr/train/config.py

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@@ -147,11 +147,6 @@ class TrainingConfig:
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gradient_checkpointing: bool = True
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gradient_checkpointing_kwargs: Dict[str, Any] = field(default_factory=lambda: {"use_reentrant": False})
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# Mixed precision
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fp16: bool = False
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bf16: bool = True
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tf32: bool = True # Enable TF32 on Ampere GPUs
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# Evaluation and checkpointing
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evaluation_strategy: str = "steps"
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eval_steps: int = 500

olmocr/train/train.py

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@@ -178,9 +178,7 @@ def main():
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adam_epsilon=config.training.adam_epsilon,
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weight_decay=config.training.weight_decay,
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max_grad_norm=config.training.max_grad_norm,
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fp16=config.training.fp16,
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bf16=config.training.bf16,
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tf32=config.training.tf32,
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bf16=True, # We're sticking with this known good reduced precision option
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eval_strategy=config.training.evaluation_strategy,
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eval_steps=config.training.eval_steps,
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save_strategy=config.training.save_strategy,

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