---
language:
- en
license: apache-2.0
datasets:
- Locutusque/InstructMixCleaned
- berkeley-nest/Nectar
pipeline_tag: text-generation
base_model: Locutusque/TinyMistral-248M
widget:
- text: '<|USER|> Design a Neo4j database and Cypher function snippet to Display Extreme
    Dental hygiene: Using Mouthwash for Analysis for Beginners. Implement if/else
    or switch/case statements to handle different conditions related to the Consent.
    Provide detailed comments explaining your control flow and the reasoning behind
    each decision. <|ASSISTANT|> '
- text: '<|USER|> Write me a story about a magical place. <|ASSISTANT|> '
- text: '<|USER|> Write me an essay about the life of George Washington <|ASSISTANT|> '
- text: '<|USER|> Solve the following equation 2x + 10 = 20 <|ASSISTANT|> '
- text: '<|USER|> Craft me a list of some nice places to visit around the world. <|ASSISTANT|> '
- text: '<|USER|> How to manage a lazy employee: Address the employee verbally. Don''t
    allow an employee''s laziness or lack of enthusiasm to become a recurring issue.
    Tell the employee you''re hoping to speak with them about workplace expectations
    and performance, and schedule a time to sit down together. Question: To manage
    a lazy employee, it is suggested to talk to the employee. True, False, or Neither?
    <|ASSISTANT|> '
inference:
  parameters:
    temperature: 0.5
    do_sample: true
    top_p: 0.5
    top_k: 30
    max_new_tokens: 250
    repetition_penalty: 1.15
model-index:
- name: TinyMistral-248M-Instruct
  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: 24.32
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-Instruct
      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: 27.52
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-Instruct
      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: 25.18
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-Instruct
      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: 41.94
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-Instruct
      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: 50.2
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-Instruct
      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: 0.0
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-Instruct
      name: Open LLM Leaderboard
---
Base model Locutusque/TinyMistral-248M fully fine-tuned on Locutusque/InstructMix. During validation, this model achieved an average perplexity of 3.23 on Locutusque/InstructMix dataset.
It has so far been trained on approximately 608,000 examples. More epochs are planned for this model.
# [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_Locutusque__TinyMistral-248M-Instruct)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |28.19|
|AI2 Reasoning Challenge (25-Shot)|24.32|
|HellaSwag (10-Shot)              |27.52|
|MMLU (5-Shot)                    |25.18|
|TruthfulQA (0-shot)              |41.94|
|Winogrande (5-shot)              |50.20|
|GSM8k (5-shot)                   | 0.00|