Weak-to-Strong Extrapolation Expedites Alignment
Collection
Better aligned models obtained by weak-to-strong model extrapolation (ExPO)
•
25 items
•
Updated
•
16
Mistral7B-PairRM-SPPO-ExPO
The extrapolated (ExPO) model based on UCLA-AGI/Mistral7B-PairRM-SPPO and mistralai/Mistral-7B-Instruct-v0.2, as in the "Weak-to-Strong Extrapolation Expedites Alignment" paper.
Specifically, we obtain this model by extrapolating (alpha = 0.3) from the weights of the SFT and DPO/RLHF checkpoints, achieving superior alignment with human preference.
This extrapolated model achieves the 35.4% win rate and 31.8% LC win rate on AlpacaEval 2.0, outperforming the original Mistral7B-PairRM-SPPO's 32.2% and 30.5%, respectively.
Evaluation Results
Evaluation results on the AlpacaEval 2.0 benchmark (you can find the evaluation outputs on the official GitHub repo):
| Win Rate (Ori) | LC Win Rate (Ori) | Win Rate (+ ExPO) | LC Win Rate (+ ExPO) | |
|---|---|---|---|---|
HuggingFaceH4/zephyr-7b-alpha |
6.7% | 10.0% | 10.6% | 13.6% |
HuggingFaceH4/zephyr-7b-beta |
10.2% | 13.2% | 11.1% | 14.0% |
berkeley-nest/Starling-LM-7B-alpha |
15.0% | 18.3% | 18.2% | 19.5% |
Nexusflow/Starling-LM-7B-beta |
26.6% | 25.8% | 29.6% | 26.4% |
snorkelai/Snorkel-Mistral-PairRM |
24.7% | 24.0% | 28.8% | 26.4% |
RLHFlow/LLaMA3-iterative-DPO-final |
29.2% | 36.0% | 32.7% | 37.8% |
internlm/internlm2-chat-1.8b |
3.8% | 4.0% | 5.2% | 4.3% |
internlm/internlm2-chat-7b |
20.5% | 18.3% | 28.1% | 22.7% |
internlm/internlm2-chat-20b |
36.1% | 24.9% | 46.2% | 27.2% |
allenai/tulu-2-dpo-7b |
8.5% | 10.2% | 11.5% | 11.7% |
allenai/tulu-2-dpo-13b |
11.2% | 15.5% | 15.6% | 17.6% |
allenai/tulu-2-dpo-70b |
15.4% | 21.2% | 23.0% | 25.7% |
Evaluation results on the MT-Bench benchmark (you can find the evaluation outputs on the official GitHub repo):
| Original | + ExPO | |
|---|---|---|
HuggingFaceH4/zephyr-7b-alpha |
6.85 | 6.87 |
HuggingFaceH4/zephyr-7b-beta |
7.02 | 7.06 |
berkeley-nest/Starling-LM-7B-alpha |
7.82 | 7.91 |
Nexusflow/Starling-LM-7B-beta |
8.10 | 8.18 |
snorkelai/Snorkel-Mistral-PairRM |
7.63 | 7.69 |
RLHFlow/LLaMA3-iterative-DPO-final |
8.08 | 8.45 |
internlm/internlm2-chat-1.8b |
5.17 | 5.26 |
internlm/internlm2-chat-7b |
7.72 | 7.80 |
internlm/internlm2-chat-20b |
8.13 | 8.26 |
allenai/tulu-2-dpo-7b |
6.35 | 6.38 |
allenai/tulu-2-dpo-13b |
7.00 | 7.26 |
allenai/tulu-2-dpo-70b |
7.79 | 8.03 |
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 13.47 |
| IFEval (0-Shot) | 36.73 |
| BBH (3-Shot) | 13.68 |
| MATH Lvl 5 (4-Shot) | 0.91 |
| GPQA (0-shot) | 3.58 |
| MuSR (0-shot) | 8.66 |
| MMLU-PRO (5-shot) | 17.24 |
- Downloads last month
- 3,449
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for chujiezheng/Mistral7B-PairRM-SPPO-ExPO
Collection including chujiezheng/Mistral7B-PairRM-SPPO-ExPO
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard36.730
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard13.680
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard0.910
- acc_norm on GPQA (0-shot)Open LLM Leaderboard3.580
- acc_norm on MuSR (0-shot)Open LLM Leaderboard8.660
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard17.240