--- language: - en license: apache-2.0 library_name: transformers datasets: - monology/VMware-open-instruct-higgsfield pipeline_tag: text-generation model-index: - name: openinstruct-mistral-7b results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 59.73 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 82.77 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 60.55 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 48.76 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 79.56 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 50.49 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=monology/openinstruct-mistral-7b name: Open LLM Leaderboard --- # OpenInstruct Mistral-7B **1st among commercially-usable 7B models on the Open LLM Leaderboard!\*** This is [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) finetuned on [VMware/open-instruct](https://huggingface.co/datasets/VMware/open-instruct). Quantized to FP16 and released under the [Apache-2.0](https://choosealicense.com/licenses/apache-2.0) license by myself. Compute generously provided by [Higgsfield AI](https://higgsfield.ai/model/655559e6b5777dab620095e0). ## Prompt format: Alpaca ``` Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: [your instruction goes here] ### Response: ``` ## Recommended preset: - temperature: 0.2 - top_k: 50 - top_p 0.95 - repetition_penalty: 1.1 \*as of 21 Nov 2023. "commercially-usable" includes both an open-source base model and a *non-synthetic* open-source finetune dataset. updated leaderboard results available [here](https://huggingfaceh4-open-llm-leaderboard.hf.space). # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_monology__openinstruct-mistral-7b) | Metric |Value| |---------------------------------|----:| |Avg. |63.64| |AI2 Reasoning Challenge (25-Shot)|59.73| |HellaSwag (10-Shot) |82.77| |MMLU (5-Shot) |60.55| |TruthfulQA (0-shot) |48.76| |Winogrande (5-shot) |79.56| |GSM8k (5-shot) |50.49|