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README.md
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@@ -27,13 +27,26 @@ Deita Llama2 13B V1.0 SFT is a fine-tuned version of Llama 2 that was trained on
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- **Model Family:** Other models and the dataset are found in the [Deita collection](https://huggingface.co/collections/hkust-nlp/deita-6569c198c174808d94cf5bd4).
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## Performance
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|------------------------------------------------|-----------|------------|----------|---------------|----------------|
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| **Proprietary Models** | | | | | |
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| GPT-4-Turbo | ? | -- | 9.32 | 97.70 | -- |
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| GPT-4 | SFT + PPO | -- | 8.99 | 95.03 | -- |
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| Claude-2 | SFT + PPO | -- | 8.06 | 91.36 | -- |
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| GPT-3.5-turbo | SFT + PPO | -- | 7.94 | 89.37 | -- |
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| **Open-sourced Models based on LLaMA-2-13B** | | | | | |
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| Tulu-2-13B | SFT | 326K SFT | 6.70 | 78.90 | -- |
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| Tulu-2-13B+DPO | SFT + DPO | 326K SFT + 60K DPO | 7.00 | 89.50 | -- |
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| Vicuna-13B-v1.5 | SFT | 125K SFT | 6.57 | 78.80 | 61.63 |
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| Random | SFT | 10K SFT | 5.78 | 65.19 | 61.32 |
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| DEITA-LLaMA2-13B-v1.0-sft | SFT | 10K SFT | 6.79 | 81.09 | 62.71 |
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## Input Format
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- **Model Family:** Other models and the dataset are found in the [Deita collection](https://huggingface.co/collections/hkust-nlp/deita-6569c198c174808d94cf5bd4).
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## Performance
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## Performance
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<details>
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<summary>See full evaluations</summary>
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| Model | Align | Data Size | MT-Bench | AlpacaEval(%) | OpenLLM (Avg.) |
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|------------------------------------------------|-----------|------------|----------|---------------|----------------|
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| **Proprietary Models** | | | | | |
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| GPT-4-Turbo | ? | -- | 9.32 | 97.70 | -- |
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| GPT-4 | SFT + PPO | -- | 8.99 | 95.03 | -- |
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| Claude-2 | SFT + PPO | -- | 8.06 | 91.36 | -- |
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| GPT-3.5-turbo | SFT + PPO | -- | 7.94 | 89.37 | -- |
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| **Open-sourced Models based on LLaMA-1-13B** | | | | | |
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| LIMA | SFT | 1K SFT | 4.29 | 41.98 | 59.82 |
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| WizardLM-13B | SFT | 70K SFT | 6.35 | 75.31 | 58.96 |
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| Vicuna-13B-v1.3 | SFT | 125K SFT | 6.39 | 82.11 | 60.01 |
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| Random | SFT | 10K SFT | 6.03 | 71.52 | 60.14 |
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| DEITA-LLaMA1-13B-v1.0-sft | SFT | 10K SFT | 6.60 | 78.01 | 64.27 |
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| **Open-sourced Models based on LLaMA-2-13B** | | | | | |
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| Tulu-2-13B | SFT | 326K SFT | 6.70 | 78.90 | -- |
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| Tulu-2-13B+DPO | SFT + DPO | 326K SFT + 60K DPO | 7.00 | 89.50 | -- |
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| Vicuna-13B-v1.5 | SFT | 125K SFT | 6.57 | 78.80 | 61.63 |
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| Random | SFT | 10K SFT | 5.78 | 65.19 | 61.32 |
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| DEITA-LLaMA2-13B-v1.0-sft | SFT | 10K SFT | 6.79 | 81.09 | 62.71 |
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| **Open-sourced Models based on Mistral-7B** | | | | | |
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| Mistral-7B-Instruct-v0.1 | -- | -- | 6.84 | 69.65 | 60.45 |
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| Zephyr-7B-sft | SFT | 200K SFT | 5.32 | 75.12 | 60.93 |
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| $\text{Zephyr-7B-}\beta$ | SFT + DPO | 200K SFT + 60K DPO | 7.34 | 90.60 | 66.36 |
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| OpenChat-3.5 | C-RLFT | >> 70K C-RLFT | 7.81 | 88.51 | -- |
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| Starling-7B | C-RLFT + APA | >>70K C-RLFT + 183K APA | 8.09 | 91.99 | -- |
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| Random | SFT | 10K SFT | 5.89 | 56.90 | 61.72 |
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| DEITA-7B-v1.0-sft (6K) | SFT | 6K SFT | 7.22 | 80.78 | 64.94 |
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| DEITA-7B-v1.0-sft (10K) | SFT | 10K SFT | 7.32 | 81.67 | 64.00 |
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| DEITA-7B-v1.0 | SFT + DPO | 6K SFT + 10K DPO | 7.55 | 90.06 | 69.86 |
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</details>
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## Input Format
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