| # **ORPO** | |
| ### **`Updates (24.03.25)`** | |
| - [X] Sample script for ORPOTrainer in 🤗<a class="link" href="https://github.com/huggingface/trl">TRL</a> is added to `trl/test_orpo_trainer_demo.py` | |
| - [X] New model, 🤗<a class="link" href="https://huggingface.co/kaist-ai/mistral-orpo-capybara-7k">kaist-ai/mistral-orpo-capybara-7k</a>, is added to 🤗<a class="link" href="https://huggingface.co/collections/kaist-ai/orpo-65efef87544ba100aef30013">ORPO Collection</a> | |
| - [X] Now you can try ORPO in 🤗<a class="link" href="https://github.com/huggingface/trl">TRL</a> and <a class="link" href="https://github.com/OpenAccess-AI-Collective/axolotl">Axolotl</a>🔥 | |
| - [X] We are making general guideline for training LLMs with ORPO, stay tuned🔥 | |
| - [X] **Mistral-ORPO-β** achieved a 14.7% in the length-controlled (LC) win rate on <a class="link" href="https://tatsu-lab.github.io/alpaca_eval/">official AlpacaEval Leaderboard</a>🔥 | |
| | |
| This is the official repository for <a class="link" href="https://arxiv.org/abs/2403.07691">**ORPO: Monolithic Preference Optimization without Reference Model**</a>. The detailed results in the paper can be found in: | |
| - [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaist-ai%2Fmistral-orpo-beta) | |
| - [AlpacaEval](#alpacaeval) | |
| - [MT-Bench](#mt-bench) | |
| - [IFEval](#ifeval) | |
| ### **`Model Checkpoints`** | |
| Our models trained with ORPO can be found in: | |
| - [X] **Mistral-ORPO-Capybara-7k**: 🤗 <a class="link" href="https://huggingface.co/kaist-ai/mistral-orpo-capybara-7k">kaist-ai/mistral-orpo-capybara-7k</a> | |
| - [X] **Mistral-ORPO-⍺**: 🤗 <a class="link" href="https://huggingface.co/kaist-ai/mistral-orpo-alpha">kaist-ai/mistral-orpo-alpha</a> | |
| - [X] **Mistral-ORPO-β**: 🤗 <a class="link" href="https://huggingface.co/kaist-ai/mistral-orpo-beta">kaist-ai/mistral-orpo-beta</a> | |
| And the corresponding logs for the average log probabilities of chosen/rejected responses during training are reported in: | |
| - [X] **Mistral-ORPO-Capybara-7k**: TBU | |
| - [X] **Mistral-ORPO-⍺**: <a class="link" href="https://wandb.ai/jiwooya1000/PREF/reports/Mistral-ORPO-7B-Training-Log--Vmlldzo3MTE1NzE0?accessToken=rms6o4mg5vo3feu1bvbpk632m4cspe19l0u1p4he3othx5bgean82chn9neiile6">Wandb Report for Mistral-ORPO-⍺</a> | |
| - [X] **Mistral-ORPO-β**: <a class="link" href="https://wandb.ai/jiwooya1000/PREF/reports/Mistral-ORPO-7B-Training-Log--Vmlldzo3MTE3MzMy?accessToken=dij4qbp6dcrofsanzbgobjsne9el8a2zkly2u5z82rxisd4wiwv1rhp0s2dub11e">Wandb Report for Mistral-ORPO-β</a> | |
| | |
| ### **`AlpacaEval`** | |
| <figure> | |
| <img class="png" src="/assets/img/alpaca_blog.png" alt="Description of the image"> | |
| <figcaption><b>Figure 1.</b> AlpacaEval 2.0 score for the models trained with different alignment methods.</figcaption> | |
| </figure> | |
| | |
| ### **`MT-Bench`** | |
| <figure> | |
| <img class="png" src="/assets/img/mtbench_hf.png" alt="Description of the image"> | |
| <figcaption><b>Figure 2.</b> MT-Bench result by category.</figcaption> | |
| </figure> | |
| | |
| ### **`IFEval`** | |
| IFEval scores are measured with <a class="link" href="https://github.com/EleutherAI/lm-evaluation-harness">EleutherAI/lm-evaluation-harness</a> by applying the chat template. The scores for Llama-2-Chat (70B), Zephyr-β (7B), and Mixtral-8X7B-Instruct-v0.1 are originally reported in <a class="link" href="https://twitter.com/wiskojo/status/1739767758462877823">this tweet</a>. | |
| | **Model Type** | **Prompt-Strict** | **Prompt-Loose** | **Inst-Strict** | **Inst-Loose** | | |
| |--------------------|:-----------------:|:----------------:|:---------------:|----------------| | |
| | **Llama-2-Chat (70B)** | 0.4436 | 0.5342 | 0.5468 | 0.6319 | | |
| | **Zephyr-β (7B)** | 0.4233 | 0.4547 | 0.5492 | 0.5767 | | |
| | **Mixtral-8X7B-Instruct-v0.1** | 0.5213 | **0.5712** | 0.6343 | **0.6823** | | |
| | **Mistral-ORPO-⍺ (7B)** | 0.5009 | 0.5083 | 0.5995 | 0.6163 | | |
| | **Mistral-ORPO-β (7B)** | **0.5287** | 0.5564 | **0.6355** | 0.6619 | | |