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We used two types of datasets for post-training. Supervised finetuning data and preference data used for RLHF stage. You can actually use less than < 1M samples
by sangwulee 1y ago
We used two types of datasets for post-training. Supervised finetuning data and preference data used for RLHF stage. You can actually use less than < 1M samples to significantly boost the aesthetics. Quality matters A LOT. Quantity helps with generalisation and stability of the checkpoints though.
- lawlessone 1y agoHow is the data collected?
- sangwulee 1y agoThe highest quality finetuning data was hand curated internally. I would say our post training pipeline is quite similar to SeedDream 2.0 ~ 3.0 series from ByteDance. Similar to them, we use extensive quality filters and internal models to get the highest quality possible. Even from there, we still hand curate a hand-picked subset.
- qotgalaxy 1y ago[dead]