Update paper bibtex

README.md

@@ -50,8 +50,11 @@ model-index:
 # **Mistral-ORPO-⍺ (7B)**
 
 **Mistral-ORPO** is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) using the *odds ratio preference optimization (ORPO)*. With ORPO, the model directly learns the preference without the supervised fine-tuning warmup phase. **Mistral-ORPO-⍺** is fine-tuned exclusively on [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized).
+- **Github Repository**: https://github.com/xfactlab/orpo
 
-## Model Performance
+## 👍 **Model Performance**
+
+### 1) AlpacaEval & MT-Bench
 
 |Model Name|Size|Align|MT-Bench|AlpacaEval 1.0|AlpacaEval 2.0|
 |:--------|:--------------:|:--------------:|:-------------------:|:------------:|:------------:|
@@ -62,11 +65,18 @@ model-index:
 |Llama-2-Chat |7B|RLHF|6.27|71.37|4.96|
 |Llama-2-Chat |13B|RLHF|6.65|81.09|7.70|
 
-## MT-Bench
+### 2) IFEval
+
+| **Model Type**     | **Prompt-Strict** | **Prompt-Loose** | **Inst-Strict** | **Inst-Loose** |
+|--------------------|:-----------------:|:----------------:|:---------------:|:--------------:|
+| **Mistral-ORPO-⍺** |       0.5009      |      0.5083      |      0.5995     |     0.6163     |
+| **Mistral-ORPO-β** |       0.5287      |      0.5564      |      0.6355     |     0.6619     |
+
+## 🗺️ **MT-Bench by Category**
 
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6415c043486c7c9a5d151583/zZvNuUFVLp6jeSvYIbdDN.png)
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6415c043486c7c9a5d151583/1Ifpt0ljCfJPEoZAqlqqy.png)
 
-## Inference
+## 🖥️ **Inference**
 
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
@@ -92,4 +102,17 @@ response = tokenizer.batch_decode(output)
 #Hi! How are you doing?</s>
 #<|assistant|>
 #I'm doing well, thank you! How are you?</s>
+```
+
+## 📎 **Citation**
+
+```
+@misc{hong2024orpo,
+      title={ORPO: Monolithic Preference Optimization without Reference Model}, 
+      author={Jiwoo Hong and Noah Lee and James Thorne},
+      year={2024},
+      eprint={2403.07691},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
 ```