Update README.md

README.md

@@ -30,13 +30,17 @@ configs:
   - split: train
     path: data/train-*
 ---
+
+# crumb/c4-benchfilter-nano
+
+A derivation of the first 3M samples from the C4 dataset.
+
 The estimated top 10% of highest n-token (mean 3,4,5) overlaps for each of the 
 selected benchmark datasets (arc, truthful_qa, hellaswag, mmlu, humaneval) based 
 on 1k samples, within the first 3M samples of C4. The top scoring sample 
 datasets for each benchmark are then filtered again for top 30% scores and 
 combined and exact-match de-duplicated. Then the top 3% scores are removed
 because they likely have exact large n-token matches by chance such as exact 
-dates or times that aren't actually relevant to the data.
+dates or times that aren't actually relevant to the data.\* 
 
-This is meant to fascilitate a high-quality short continuation of pretraining 
-for language models.
+\*Upon further examination, some of these samples are still present throughout the data, you might benefit from using `dataset.filter(x['score'] > thresh)` for some threshold, but you risk losing high quality samples as well, this tradeoff should be well-examined before training.