Update README.md

README.md

@@ -27,7 +27,7 @@ As same as 42dot-PLM, the model is built upon a Transformer decoder architecture
 (\* unit: tokens)
 ### Supervised Fine-tuning
 
-Fine-tuning took about 20 hours using 8 * NVIDIA A100 GPUs. For the training dataset, we manually constructed  (question or insturuction) and response pairs, which can either be single- or multi-turn. 
+Fine-tuning took about 112 GPU hours (in NVIDIA A100). For the training dataset, we manually constructed  (question or insturuction) and response pairs, which can either be single- or multi-turn. 
 
 ### Evaluation
 Inspired by recent attempts like [Vicuna](https://lmsys.org/blog/2023-03-30-vicuna/#how-good-is-vicuna), we evaluate 42dot-PLM with other proprietary/open-sourced chatbots using GPT-4 for assessing various aspects of responses. The evaluation dataset consists of 121 prompts over 10 categories. The sample of the evaluation dataset and prompt template can be downloaded from our [GitHub repo](https://github.com/42dot/42dot_LLM).