Update README.md

README.md

@@ -49,6 +49,23 @@ for output in outputs:
     print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
 ```
 
+# Evaluation scores
+
+We find that this is the best performing model in the 7/8B class of LLMs on a multitude of Japanese language benchmarks.
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/64b63f8ad57e02621dc93c8b/2obyDbrjiNV3PGfwom6EI.png)
+
+# Training data
+
+We train on three sources of data to create this model
+
+* [megagonlabs/instruction_ja](https://github.com/megagonlabs/instruction_ja) - 669 conversations
+    * A hand-edited dataset of nearly 700 conversations taken originally from translations of the [kunishou/hh-rlhf-49k-ja](https://huggingface.co/datasets/kunishou/hh-rlhf-49k-ja) dataset.
+* [openchat/openchat_sharegpt4_dataset](https://huggingface.co/datasets/openchat/openchat_sharegpt4_dataset/resolve/main/sharegpt_gpt4.json) (Japanese conversations only) - 167 conversations
+    * Conversations taken from humans talking to GPT-4
+* lightblue/tagengo-gpt4 (Japanese prompts only) (Link coming soon!) - 2,482 conversations
+    * Almost 2,500 diverse Japanese prompts sampled from [lmsys/lmsys-chat-1m](https://huggingface.co/datasets/lmsys/lmsys-chat-1m) and then used to prompt `gpt-4-0125-preview`
+
 # Training config
 
 [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
@@ -118,23 +135,6 @@ special_tokens:
 
 </details><br>
 
-# workspace/llm_training/axolotl/llama3-ja/output_openchat_megagon_lbgpt4_ja_8B_instruct
-
-This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.9555
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
 
 ## Training procedure