Update README.md (#6)

- Update README.md (452c846f35ea67b263d50044f60f0d1a3085c672)


Co-authored-by: Ariel Lee <[email protected]>

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}
 }
 ```