Add _metrics dict to Trainer for custom metric logging#43636
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abigailtech wants to merge 2 commits intohuggingface:mainfrom
Open
Add _metrics dict to Trainer for custom metric logging#43636abigailtech wants to merge 2 commits intohuggingface:mainfrom
abigailtech wants to merge 2 commits intohuggingface:mainfrom
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qgallouedec
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Feb 3, 2026
| self._memory_tracker = TrainerMemoryTracker(self.args.skip_memory_metrics) | ||
| self._memory_tracker.start() | ||
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| self._metrics = {"train": defaultdict(list), "eval": defaultdict(list)} |
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I'm wondering if we can leverage this self._metrics to log the loss
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though about it, but loss uses tensor accumulation to avoid TPU sync overhead. metrics is more for auxiliary custom metrics that don't need that optimization
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Adds a private _metrics dict to the Trainer class that allows custom trainers to log metrics without overriding log.
Custom trainers can now simply do:
self._metrics[mode]["my_metric"].append(value)And the metrics will be automatically averaged, merged into logs and cleared when log() is called.
Fixes #43599