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fix dpo metrics

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hiyouga
2024-11-02 19:22:11 +08:00
parent 07e5088851
commit 4270f7dfb9
7 changed files with 143 additions and 58 deletions
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31
src/llamafactory/train/callbacks.py
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@@ -287,13 +287,13 @@ class LogCallback(TrainerCallback):
logs = dict(
current_steps=self.cur_steps,
total_steps=self.max_steps,
loss=state.log_history[-1].get("loss", None),
eval_loss=state.log_history[-1].get("eval_loss", None),
predict_loss=state.log_history[-1].get("predict_loss", None),
reward=state.log_history[-1].get("reward", None),
accuracy=state.log_history[-1].get("rewards/accuracies", None),
learning_rate=state.log_history[-1].get("learning_rate", None),
epoch=state.log_history[-1].get("epoch", None),
loss=state.log_history[-1].get("loss"),
eval_loss=state.log_history[-1].get("eval_loss"),
predict_loss=state.log_history[-1].get("predict_loss"),
reward=state.log_history[-1].get("reward"),
accuracy=state.log_history[-1].get("rewards/accuracies"),
lr=state.log_history[-1].get("learning_rate"),
epoch=state.log_history[-1].get("epoch"),
percentage=round(self.cur_steps / self.max_steps * 100, 2) if self.max_steps != 0 else 100,
elapsed_time=self.elapsed_time,
remaining_time=self.remaining_time,
@@ -304,16 +304,17 @@ class LogCallback(TrainerCallback):
if os.environ.get("RECORD_VRAM", "0").lower() in ["true", "1"]:
vram_allocated, vram_reserved = get_peak_memory()
logs["vram_allocated"] = round(vram_allocated / 1024 / 1024 / 1024, 2)
logs["vram_reserved"] = round(vram_reserved / 1024 / 1024 / 1024, 2)
logs["vram_allocated"] = round(vram_allocated / (1024**3), 2)
logs["vram_reserved"] = round(vram_reserved / (1024**3), 2)
logs = {k: v for k, v in logs.items() if v is not None}
if self.webui_mode and all(key in logs for key in ["loss", "learning_rate", "epoch"]):
logger.info_rank0(
"{{'loss': {:.4f}, 'learning_rate': {:2.4e}, 'epoch': {:.2f}, 'throughput': {}}}".format(
logs["loss"], logs["learning_rate"], logs["epoch"], logs.get("throughput", "N/A")
)
)
if self.webui_mode and all(key in logs for key in ("loss", "lr", "epoch")):
log_str = f"'loss': {logs['loss']:.4f}, 'learning_rate': {logs['lr']:2.4e}, 'epoch': {logs['epoch']:.2f}"
for extra_key in ("reward", "accuracy", "throughput"):
if logs.get(extra_key):
log_str += f", '{extra_key}': {logs[extra_key]:.2f}"
logger.info_rank0("{" + log_str + "}")
if self.thread_pool is not None:
self.thread_pool.submit(self._write_log, args.output_dir, logs)