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Model: chujiezheng/Mistral7B-PairRM-SPPO-ExPO
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README.md

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+---
+language:
+- en
+license: apache-2.0
+model-index:
+- name: Mistral7B-PairRM-SPPO-ExPO
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: HuggingFaceH4/ifeval
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 36.73
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: BBH
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 13.68
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: hendrycks/competition_math
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 0.91
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 3.58
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 8.66
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 17.24
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO
+      name: Open LLM Leaderboard
+---
+
+# Mistral7B-PairRM-SPPO-ExPO
+
+The extrapolated (ExPO) model based on [`UCLA-AGI/Mistral7B-PairRM-SPPO`](https://huggingface.co/UCLA-AGI/Mistral7B-PairRM-SPPO) and [`mistralai/Mistral-7B-Instruct-v0.2`](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2), as in the "[Weak-to-Strong Extrapolation Expedites Alignment](https://arxiv.org/abs/2404.16792)" 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](https://github.com/chujiezheng/LLM-Extrapolation/tree/main/results_alpaca)):
+
+|                                      | 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](https://github.com/chujiezheng/LLM-Extrapolation/tree/main/results_mtbench)):
+
+|                                      | 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](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_chujiezheng__Mistral7B-PairRM-SPPO-ExPO)
+
+|      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|
+

config.json

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+{
+  "_name_or_path": "UCLA-AGI/Mistral7B-PairRM-SPPO",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.40.1",
+  "use_cache": false,
+  "vocab_size": 32000
+}

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+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "transformers_version": "4.40.1"
+}

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special_tokens_map.json

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+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "rstrip": false,
+    "single_word": false
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+    "normalized": false,
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+    "single_word": false
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+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+      "single_word": false,
+      "special": true
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+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 2048,
+  "pad_token": "</s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}