Update README.md

README.md

@@ -20,10 +20,10 @@ the Multicultural Classroom Discourse Dataset [Rapanta et al., 2021](https://www
 MathDial [Macina et al., 2023](https://aclanthology.org/2023.findings-emnlp.372), and 
 Conversational Uptake [Demszky et al., 2021].
 
-We are evaluating LLaMa-3 for this task. 
+We are evaluating Llama-3.1-8B for this task. 
 Instead of using programmable fine-tuning libraries such as Axolotl ([link](https://github.com/OpenAccess-AI-Collective/axolotl)) 
 or Huggingface TRL ([link](https://github.com/huggingface/trl)), 
-we are employing the more general command-line LLaMA-Factory ([link](https://github.com/hiyouga/LLaMA-Factory)) toolkit 
+we have employed the more general command-line LLaMA-Factory ([link](https://github.com/hiyouga/LLaMA-Factory)) toolkit 
 that facilitates the fine-tuning of various well-known LLMs on custom data. 
 Parameter-efficient fine-tuning is achieved via the QLoRA method [Dettmers et al., 2023](https://proceedings.neurips.cc/paper_files/paper/2023/file/1feb87871436031bdc0f2beaa62a049b-Paper-Conference.pdf).