Update README.md

README.md

@@ -87,7 +87,7 @@ near-tied questions differently.
 
 ## Training pipeline (two stages)
 
-**Stage 1 - continued pretraining.** `training/cpt_gemma4_sinhala.py` on `Minuri/diverse_sinhala_dataset` (`high_confidence_7_7M.csv`), 1M sentences, domain-balanced sampling, 16 same-domain sentences joined into each pseudo-document, packing enabled, LoRA r=128 alpha=32 with rsLoRA, 1 epoch on one A40. Result: `QBitsLK/gemma4-e4b-sinhala-cpt` (merged). Diagnostics in `training/eval_cpt_success.py` - held-out bits-per-character improved 19.6% while English perplexity regressed 21.7%.
+**Stage 1 - continued pretraining.** `training/cpt_gemma4_sinhala.py` on `Minuri/diverse_sinhala_dataset` (`high_confidence_7_7M.csv`)[Minuri/diverse_sinhala_dataset], 1M sentences, domain-balanced sampling, 16 same-domain sentences joined into each pseudo-document, packing enabled, LoRA r=128 alpha=32 with rsLoRA, 1 epoch on one A40. Result: `QBitsLK/gemma4-e4b-sinhala-cpt` (merged). Diagnostics in `training/eval_cpt_success.py` - held-out bits-per-character improved 19.6% while English perplexity regressed 21.7%.
 
 ```bash
 python training/cpt_gemma4_sinhala.py --max_sentences 1000000 --epochs 1