Update README.md

README.md

@@ -1,31 +1,55 @@
 ---
-tags:
-- generated_from_trainer
-model-index:
-- name: mistral-7b-300k-6k-a100-6e-valid-6
-  results: []
+license: apache-2.0
+datasets:
+- hkust-nlp/deita-6k-v0
+language:
+- en
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+<img src="https://huggingface.co/datasets/hkust-nlp/deita-images/resolve/main/logo-final.png" alt="Deita banner" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
 
-# mistral-7b-300k-6k-a100-6e-valid-6
+# Model Card for Deita 7B V1.0 SFT (6k)
 
-This model was trained from scratch on an unknown dataset.
+Deita is an open-sourced project designed to facilitate **Automatic Data Selection** for instruction tuning in Large Language Models (LLMs). 
+DeitaDeita 7B V1.0 SFT (6k) is a fine-tuned version of Mistral-7B-v0.1 that was trained on 6k automatically selected lightweight, high-quality alignment SFT data: [Deita 6K V0](https://huggingface.co/datasets/hkust-nlp/deita-6k-v0).
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
+- **Model type:** Model fine tuned on automatically selected lightweight, high-quality alignment SFT data.
+- **Language(s) (NLP):** Primarily English
+- **Finetuned from model:** Mistral-7B-v0.1
+
+### Model Sources
+
+- **Repository:** https://github.com/hkust-nlp/deita
+- **Model Family:** Other models and the dataset are found in the [Deita collection](https://huggingface.co/collections/hkust-nlp/deita-6569c198c174808d94cf5bd4).
+
+## Performance
+  | Model                                          | Align     | Data Size  | MT-Bench | AlpacaEval(%) | OpenLLM (Avg.) |
+|------------------------------------------------|-----------|------------|----------|---------------|----------------|
+| **Proprietary Models**                         |           |            |          |               |                |
+| GPT-4-Turbo                                    | ?         | --         | 9.32     | 97.70         | --             |
+| GPT-4                                          | SFT + PPO | --         | 8.99     | 95.03         | --             |
+| Claude-2                                       | SFT + PPO | --         | 8.06     | 91.36         | --             |
+| GPT-3.5-turbo                                  | SFT + PPO | --         | 7.94     | 89.37         | --             |
+| **Open-sourced Models based on Mistral-7B**    |           |            |          |               |                |
+| Mistral-7B-Instruct-v0.1                       | --        | --         | 6.84     | 69.65         | 60.45          |
+| Zephyr-7B-sft                                  | SFT       | 200K SFT      | 5.32     | 75.12         | 60.93          |
+| $\text{Zephyr-7B-}\beta$                       | SFT + DPO | 200K SFT + 60K DPO | 7.34     | 90.60         | 66.36          |
+| OpenChat-3.5                                   | C-RLFT | >70K C-RLFT | 7.81     | 88.51         | --           |
+| Starling-7B                                    | C-RLFT + APA | >70K C-RLFT + 183K APA | 8.09     | 91.99         | --            |
+| Random                                         | SFT       | 10K SFT       | 5.89     | 56.90         | 61.72          |
+| DEITA-7B-v1.0-sft (6K)                           | SFT       | 6K SFT       | 7.22     | 80.78         | --          |
+| DEITA-7B-v1.0-sft                           | SFT       | 10K SFT       | 7.32     | 81.67         | 64.00          |
+| DEITA-7B-v1.0             | SFT + DPO | 6K SFT + 10K DPO   | 7.44     | 89.69         | 70.32          |  
+
+## Input Format
+
+The model is trained using the [vicuna_v1.1 template](https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py)
+
+```
+A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: Hello! ASSISTANT: Hi!</s>USER: How are you? ASSISTANT:
+```
 
 ### Training hyperparameters
 
@@ -44,10 +68,6 @@ The following hyperparameters were used during training:
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 6.0
 
-### Training results
-
-
-
 ### Framework versions
 
 - Transformers 4.34.1