Update README.md

README.md

@@ -53,8 +53,8 @@ Minotaur 13B model is fine-tuned on the following openly available datasets:
   - custom sysnthetic datasets around misconceptions, in-context qa, jokes, N-tasks problems, and context-insensitivity
   - ARC-Easy & ARC-Challenge - instruct augmented for detailed responses, derived from the `train` split
   - [hellaswag](https://huggingface.co/datasets/hellaswag) - 30K+ rows of instruct augmented for detailed explanations w 30K+ rows, derived from the `train` split
-  - [riddle_sense](https://huggingface.co/datasets/riddle_sense) - instruct augmented 
-  - [gsm8k](https://huggingface.co/datasets/gsm8k) - instruct augmented
+  - [riddle_sense](https://huggingface.co/datasets/riddle_sense) - instruct augmented, derived from the `train` split
+  - [gsm8k](https://huggingface.co/datasets/gsm8k) - instruct augmented, derived from the `train` split
   - prose generation
 
 # Shoutouts
@@ -76,7 +76,7 @@ Minotaur was built with [Axolotl](https://github.com/OpenAccess-AI-Collective/ax
 
 ## Bias, Risks, and Limitations
 Minotaur has not been aligned to human preferences with techniques like RLHF or deployed with in-the-loop filtering of responses like ChatGPT, so the model can produce problematic outputs (especially when prompted to do so).
-Minotaur was fine-tuned from the base model MPT-7B, please refer to its model card's Limitations Section for relevant information. (included below)
+Minotaur was fine-tuned from the base model LLaMA-13B, please refer to its model card's Limitations Section for relevant information. (included below)
 
 ## Benchmarks