README.md

---
license: apache-2.0
library_name: transformers
datasets:
- andysalerno/ansalern-nectar-inputoutput
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: mistral-sft-v3
  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: 61.35
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=andysalerno/mistral-sft-v3
      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: 82.23
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=andysalerno/mistral-sft-v3
      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: 63.4
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=andysalerno/mistral-sft-v3
      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: 48.49
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=andysalerno/mistral-sft-v3
      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: 77.66
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=andysalerno/mistral-sft-v3
      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: 32.45
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=andysalerno/mistral-sft-v3
      name: Open LLM Leaderboard
---

This is [mistralai/Mistral-7B-v0.1](https://huggingface.co./mistralai/Mistral-7B-v0.1), but with the special tokens added for ChatML, and then lightly finetuned with sft using a ChatML formatted dataset: [andysalerno/ansalern-nectar-inputoutput](https://huggingface.co./datasets/andysalerno/ansalern-nectar-inputoutput)

The training was very light, so while this model correctly follows ChatML formatting, it is not intended to be a chat model.

Rather, it is intended to be a base for further fine-tuning models that will use ChatML.
# [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_andysalerno__mistral-sft-v3)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |60.93|
|AI2 Reasoning Challenge (25-Shot)|61.35|
|HellaSwag (10-Shot)              |82.23|
|MMLU (5-Shot)                    |63.40|
|TruthfulQA (0-shot)              |48.49|
|Winogrande (5-shot)              |77.66|
|GSM8k (5-shot)                   |32.45|