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Adding Evaluation Results (#1)
Browse files- Adding Evaluation Results (9e60d7aeb40d21d113768fc1b28ffdbbaa0ddb92)
Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>
README.md
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---
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license: apache-2.0
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---
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This model was created as an experiment on using LoRA extraction to replicate [Openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106) using [Mistral-7B-v0.2](https://huggingface.co/mistral-community/Mistral-7B-v0.2) as a base model instead of the original [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
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@@ -12,4 +107,17 @@ Openchat-3.5-0106 is an excellent model but was based on Mistral-7B-v0.1 which h
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This is the result. This model is not meant for use, it was created to test if this method is viable for replacing the base model of fine-tuned models (when tokenizer and weights have not been changed too much). I am uploading here for evaluation. I don't expect this model to match the original OpenChat-3.5-0106 since I used a LoRA with rank 512, so it won't be equivalent to a full fine-tuning. I have been able to extract LoRAs with higher rank, but currently I don't have the resources to merge them with the model as the memory requirements exceed what I have at my disposal.
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If you would like to help my work, check my Ko-Fi and/or Patreon:
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* https://ko-fi.com/pretergeek
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-
* https://patreon.com/Pretergeek
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---
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license: apache-2.0
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model-index:
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- name: openchat-3.5-0106_Rebased_Mistral-7B-v0.2
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 37.06
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name: strict accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Pretergeek/openchat-3.5-0106_Rebased_Mistral-7B-v0.2
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 10.91
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Pretergeek/openchat-3.5-0106_Rebased_Mistral-7B-v0.2
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 3.85
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name: exact match
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Pretergeek/openchat-3.5-0106_Rebased_Mistral-7B-v0.2
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 2.91
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Pretergeek/openchat-3.5-0106_Rebased_Mistral-7B-v0.2
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 20.57
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Pretergeek/openchat-3.5-0106_Rebased_Mistral-7B-v0.2
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 20.33
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Pretergeek/openchat-3.5-0106_Rebased_Mistral-7B-v0.2
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name: Open LLM Leaderboard
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---
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This model was created as an experiment on using LoRA extraction to replicate [Openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106) using [Mistral-7B-v0.2](https://huggingface.co/mistral-community/Mistral-7B-v0.2) as a base model instead of the original [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
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This is the result. This model is not meant for use, it was created to test if this method is viable for replacing the base model of fine-tuned models (when tokenizer and weights have not been changed too much). I am uploading here for evaluation. I don't expect this model to match the original OpenChat-3.5-0106 since I used a LoRA with rank 512, so it won't be equivalent to a full fine-tuning. I have been able to extract LoRAs with higher rank, but currently I don't have the resources to merge them with the model as the memory requirements exceed what I have at my disposal.
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If you would like to help my work, check my Ko-Fi and/or Patreon:
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* https://ko-fi.com/pretergeek
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+
* https://patreon.com/Pretergeek
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Pretergeek__openchat-3.5-0106_Rebased_Mistral-7B-v0.2)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |15.94|
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|IFEval (0-Shot) |37.06|
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|BBH (3-Shot) |10.91|
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|MATH Lvl 5 (4-Shot)| 3.85|
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|GPQA (0-shot) | 2.91|
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|MuSR (0-shot) |20.57|
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|MMLU-PRO (5-shot) |20.33|
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