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#NewPaperAlert When and where does pretraining (PT) data matter?

We conduct the largest published PT data study, varying:
1⃣ Corpus age
2⃣ Quality/toxicity filters
3⃣ Domain composition

We have several recs for model creators…
📜: bit.ly/3WxsxyY

1/ 🧵 Image
First, PT data selection is mired in mysticism.

1⃣ Documentation Debt: #PALM2 & #GPT4 don't document their data
2⃣ PT is expensive ➡️ experiments are sparse
3⃣ So public data choices are largely guided by ⚡️intuition, rumors, and partial info⚡️

2/ Image
PT is the foundation of data-centric and modern LMs. This research was expensive but important to shed light on open questions in training data design.

Here are our main findings:

3/
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