Update README.md

README.md

@@ -40,8 +40,8 @@ VBART is the first sequence-to-sequence LLM pre-trained on Turkish corpora from
 The model is capable of conditional text generation tasks such as text summarization, paraphrasing, and title generation when fine-tuned.
 It outperforms its multilingual counterparts, albeit being much smaller than other implementations.
 
-VBART-XLarge is an experimental version of original VBART-Large. VBart-XLarge created using copying original weights of VBart-Large and adding extra layers between them and trained with %88 less data.
-VBART-XLarge gives improved results compared to VBART-Large albeit being small.
+VBART-XLarge is an experimental version of original VBART-Large. VBart-XLarge created using copying original weights of VBart-Large and adding extra layers between original weights. It is exposed to %88 less tokens compared to VBart-Large.
+VBART-XLarge gives improved results compared to VBART-Large albeit in small margins.
 
 This repository contains fine-tuned TensorFlow and Safetensors weights of VBART for question-answering and generation tasks described in the [paper](https://doi.org/10.55730/1300-0632.3914).