add throughput entry to log
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82a565362c
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@ -170,12 +170,14 @@ class LogCallback(TrainerCallback):
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percentage=round(self.cur_steps / self.max_steps * 100, 2) if self.max_steps != 0 else 100,
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percentage=round(self.cur_steps / self.max_steps * 100, 2) if self.max_steps != 0 else 100,
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elapsed_time=self.elapsed_time,
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elapsed_time=self.elapsed_time,
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remaining_time=self.remaining_time,
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remaining_time=self.remaining_time,
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throughput="{:.2f}".format(state.num_input_tokens_seen / (time.time() - self.start_time)),
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total_tokens=state.num_input_tokens_seen,
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)
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)
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logs = {k: v for k, v in logs.items() if v is not None}
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logs = {k: v for k, v in logs.items() if v is not None}
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if self.webui_mode and all(key in logs for key in ["loss", "learning_rate", "epoch"]):
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if self.webui_mode and all(key in logs for key in ["loss", "learning_rate", "epoch"]):
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logger.info(
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logger.info(
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"{{'loss': {:.4f}, 'learning_rate': {:2.4e}, 'epoch': {:.2f}}}".format(
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"{{'loss': {:.4f}, 'learning_rate': {:2.4e}, 'epoch': {:.2f}, 'throughput': {}}}".format(
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logs["loss"], logs["learning_rate"], logs["epoch"]
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logs["loss"], logs["learning_rate"], logs["epoch"], logs["throughput"]
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)
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)
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)
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)
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@ -132,6 +132,7 @@ class Runner:
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pure_bf16=(get("train.compute_type") == "pure_bf16"),
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pure_bf16=(get("train.compute_type") == "pure_bf16"),
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plot_loss=True,
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plot_loss=True,
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ddp_timeout=180000000,
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ddp_timeout=180000000,
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include_num_input_tokens_seen=True,
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)
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)
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# checkpoints
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# checkpoints
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