README.md

---
license: llama3
language:
- tr
- en
base_model: meta-llama/Meta-Llama-3-8B-Instruct
model-index:
- name: MARS
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge TR
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc
      value: 46.08
      name: accuracy
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU TR
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 47.02
      name: accuracy
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA TR
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: acc
      name: accuracy
      value: 49.38
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande TR
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 53.71
      name: accuracy
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k TR
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 53.08
      name: accuracy
pipeline_tag: text-generation
---


<img src="MARS-1.0.png" alt="Curiosity MARS model logo" style="border-radius: 1rem; width: 100%">


<div style="display: flex; justify-content: center; align-items: center; flex-direction: column">
    <h1 style="font-size: 5em; margin-bottom: 0; padding-bottom: 0;">MARS</h1>
    <aside>by <a href="https://curiosity.tech">Curiosity Technology</a></aside>
</div>

MARS is the first iteration of Curiosity Technology models, based on Llama 3 8B.

We have trained MARS on in-house Turkish dataset, as well as several open-source datasets and their Turkish
translations.
It is our intention to release Turkish translations in near future for community to have their go on them.

MARS have been tranied for 3 days on 4xA100.

## Model Details

- **Base Model**: Meta Llama 3 8B Instruct
- **Training Dataset**: In-house & Translated Open Source Turkish Datasets
- **Training Method**: LoRA Fine Tuning