Update README.md

README.md

@@ -8,21 +8,20 @@ language:
 # EvoLLM-v1-JP-7B
 
 <!-- Provide a quick summary of what the model is/does. -->
-EvoLLM-v1-JP-7B is a evolved Japanese Math LLM.
+EvoLLM-v1-JP-7B is a evolved Japanese Math LLM. 
 
 ## Model Details
 
 ### Model Description
 
 <!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+EvoLLM-v1-JP-7B is a Japanese Math LLM, merged the following source models in the Parameter Space (PS) by using an evolutionary approach. 
 
 - **Developed by:** [Sakana AI](https://sakana.ai/)
 - **Model type:** Autoregressive Language Model
 - **Language(s):** Japanese
 - **License:** [MICROSOFT RESEARCH LICENSE TERMS](./LICENSE)
-- **Base models for merge:**
+- **Source models:**
   - [augmxnt/shisa-gamma-7b-v1](https://huggingface.co/augmxnt/shisa-gamma-7b-v1)
   - [WizardLM/WizardMath-7B-V1.1](https://huggingface.co/WizardLM/WizardMath-7B-V1.1)
   - [GAIR/Abel-7B-002](https://huggingface.co/GAIR/Abel-7B-002)
@@ -72,12 +71,21 @@ print(generated_text)
 
 ## Evaluation
 
-TODO: Table & Link to Github to reproduce 
+We present the results that compares the performance of the our evolved LLMs compared to the source LLMs. To reproduce the results, please use [our Github repository](https://github.com/SakanaAI/evolving-merged-models).
+
+![eval-results](./evollm-math-results.png)
 
 
 ## Citation
 
 ```bibtex
-
+@misc{sakana2024evofactory,
+      title         = {Evolutionary Optimization of Model Merging Recipes}, 
+      author.       = {Takuya Akiba and Makoto Shing and Yujin Tang and Qi Sun and David Ha},
+      year          = {2024},
+      eprint        = {TODO},
+      archivePrefix = {arXiv},
+      primaryClass  = {cs.CV}
+}
 ```