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fix for training stability on single GPU
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train.py
3
train.py
@ -45,7 +45,7 @@ wandb_project = 'owt'
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wandb_run_name = 'gpt2' # 'run' + str(time.time())
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# data
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dataset = 'openwebtext'
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gradient_accumulation_steps = 1 # used to simulate larger batch sizes
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gradient_accumulation_steps = 5 # used to simulate larger batch sizes
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batch_size = 12 # if gradient_accumulation_steps > 1, this is the micro-batch size
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block_size = 1024
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# model
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@ -92,6 +92,7 @@ else:
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# if not ddp, we are running on a single gpu, and one process
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master_process = True
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seed_offset = 0
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gradient_accumulation_steps *= 8 # simulate 8 gpus
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if master_process:
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os.makedirs(out_dir, exist_ok=True)
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