Update README.md

README.md

@@ -176,6 +176,19 @@ We used a VM with 8 x A100 40GB hosted in Lambda Labs, but while experimenting w
 
 We used a a new curated version of [`openbmb/UltraFeedback`](https://huggingface.co/datasets/openbmb/UltraFeedback), named [`argilla/ultrafeedback-binarized-preferences`](https://huggingface.co/argilla/ultrafeedback-binarized-preferences).
 
+TLDR:
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+After visually browsing around some examples using the sort and filter feature of Argilla (sort by highest rating for chosen responses), we noticed a strong mismatch between the `overall_score` in the original UF dataset (and the Zephyr train_prefs dataset) and the quality of the chosen response. 
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+By adding the critique rationale to our Argilla Dataset, we confirmed the critique rationale was highly negative, whereas the rating was very high (the highest in fact: `10`). 
+See screenshot below for one example of this issue. 
+After some quick investigation, we identified hundreds of examples having the same issue, reported a bug on the UltraFeedback repo, and informed the H4 team.
+
+While we're working on fixing the original dataset (already narrowed down ~2K problematic examples). We decided to leverage the multi-preference ratings, leading to Notus!
+
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+![image/png](https://cdn-uploads.huggingface.co/production/uploads/60420dccc15e823a685f2b03/M9qCKyAB_G1MbVBAPeitd.png)
+
 ## Prompt template
 
 We use the same prompt template as [`HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta):