Update README.md

README.md

@@ -13,15 +13,17 @@ metrics:
 
 # 🥳 Platypus-30B has arrived! 
 
-Platypus-30B is an instruction fine-tuned model based on the LLaMA-30B transformer architecture and takes advantage of LoRA.
+Platypus-30B is an instruction fine-tuned model based on the LLaMA-30B transformer architecture.
 
 | Metric                | Value |
 |-----------------------|-------|
-| MMLU (5-shot)         | 65.4  |
+| MMLU (5-shot)         | 64.2  |
 | ARC (25-shot)         | 64.6  |
 | HellaSwag (10-shot)   | 84.3  |
 | TruthfulQA (0-shot)   | 45.8  |
-| Avg.                  | 65    | 
+| Avg.                  | 64.7  | 
+
+We use state-of-the-art [Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) to run the benchmark tests above.
 
 ## Model Details
 
@@ -58,17 +60,11 @@ The base LLaMA model is trained on various data, some of which may contain offen
   journal={arXiv preprint arXiv:2302.13971},
   year={2023}
 }
-@article{DBLP:journals/corr/abs-2106-09685,
-  author       = {Edward J. Hu and
-                  Yelong Shen and
-                  Phillip Wallis and
-                  Zeyuan Allen{-}Zhu and
-                  Yuanzhi Li and
-                  Shean Wang and
-                  Weizhu Chen},
-  title        = {LoRA: Low-Rank Adaptation of Large Language Models},
-  journal      = {CoRR},
-  year         = {2021},
-  url          = {https://arxiv.org/abs/2106.09685},
+
+@article{hu2021lora,
+  title={LoRA: Low-Rank Adaptation of Large Language Models},
+  author={Hu, Edward J. and Shen, Yelong and Wallis, Phillip and Allen-Zhu, Zeyuan and Li, Yuanzhi and Wang, Shean and Chen, Weizhu},
+  journal={CoRR},
+  year={2021}
 }
 ```