license: cc-by-4.0
datasets:
- Open-Orca/OpenOrca
- Intel/orca_dpo_pairs
language:
- en
tags:
- xDAN-AI
- OpenOrca
- DPO
- Self-Think
Top 1 Performer on MT-bench🏆
**The first top-performing 7b model at Humanities, Coding and Writing.**
xDAN-AI • > Discord • Twitter • Huggingface
Outperforms GPT-3.5-turbo & Claude-v1
Approaches GPT-4 on MT-Bench
########## First turn ##########
| model | turn | score | size |
|---|---|---|---|
| gpt-4 | 1 | 8.95625 | - |
| xDAN-L1-Chat-RL-v1 | 1 | 8.87500 | 7b |
| xDAN-L2-Chat-RL-v2 | 1 | 8.78750 | 30b |
| claude-v1 | 1 | 8.15000 | - |
| gpt-3.5-turbo | 1 | 8.07500 | 20b |
| vicuna-33b-v1.3 | 1 | 7.45625 | 33b |
| wizardlm-30b | 1 | 7.13125 | 30b |
| oasst-sft-7-llama-30b | 1 | 7.10625 | 30b |
| Llama-2-70b-chat | 1 | 6.98750 | 70b |
########## Second turn ##########
| model | turn | score | size |
|---|---|---|---|
| gpt-4 | 2 | 9.025000 | - |
| xDAN-L2-Chat-RL-v2 | 2 | 8.087500 | 30b |
| xDAN-L1-Chat-RL-v1 | 2 | 7.825000 | 7b |
| gpt-3.5-turbo | 2 | 7.812500 | 20b |
| claude-v1 | 2 | 7.650000 | - |
| wizardlm-30b | 2 | 6.887500 | 30b |
| vicuna-33b-v1.3 | 2 | 6.787500 | 33b |
| Llama-2-70b-chat | 2 | 6.725000 | 70b |
########## Average turn##########
| model | score | size |
|---|---|---|
| gpt-4 | 8.990625 | - |
| xDAN-L2-Chat-RL-v2 | 8.437500 | 30b |
| xDAN-L1-Chat-RL-v1 | 8.350000 | 7b |
| gpt-3.5-turbo | 7.943750 | 20b |
| claude-v1 | 7.900000 | - |
| vicuna-33b-v1.3 | 7.121875 | 33b |
| wizardlm-30b | 7.009375 | 30b |
| Llama-2-70b-chat | 6.856250 | 70b |
LM-Evaluation-Harness
| Task | Score |
|---|---|
| Average | 68.38 |
| ARC | 66.3 |
| HellaSwag | 85.81 |
| MMLU | 63.21 |
| TruthfulQA | 56.7 |
| Winogrande | 78.85 |
| GSM8K | 59.44 |
Prompt Template: Alpaca
You are a helpful assistant named DAN. You are an expert in worldly knowledge, skilled in employing a probing questioning strategy, and you carefully consider each step before providing answers. \n\n### Instruction:\n{instruction}\n\n### Response:
Dataset:
- Selected from OpenOrca
- Intel Orca-DPO-Pairs
- Privately Crafted Dataset
Training:
- SFT with Mixed dataset from OpenOrca & Intel
- The DPO-v2 dataset
- The DPO-v2 Trainer
Created By xDAN-AI at 2023-12-15
Eval by FastChat: https://github.com/lm-sys/FastChat.git
Disclaimer
We employ rigorous data compliance validation algorithms throughout the training of our language model to ensure the highest level of compliance. However, due to the intricate nature of data and the wide range of potential usage scenarios for the model, we cannot guarantee that it will consistently produce accurate and sensible outputs. Users should be aware of the possibility of the model generating problematic results. Our organization disclaims any responsibility for risks or issues arising from misuse, improper guidance, unlawful usage, misinformation, or subsequent concerns regarding data security.
About xDAN-AI
xDAN-AI represents the forefront of Silicon-Based Life Factory technology. For comprehensive information and deeper insights into our cutting-edge technology and offerings, please visit our website: https://www.xdan.ai.