Update README.md

README.md

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 <details>
   <summary>Some more details about the evaluation.</summary>
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 - All the evaluation context length is determined by the llama-2 tokenizer to accommodate models with smaller vocabularies.
 - For Json KV and RAG, we randomly sample positions of the target key-value pairs or the passages to test “lost-in-the-middle”.
 - For ICL, we use abstract labels (0,1,2,3…) instead of natural language labels ([Pan et al., 2023](https://arxiv.org/pdf/2305.09731)) to evaluate models’ ability to learn new tasks.
 - We use greedy decoding for all models/tasks.
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 </details>