README.md

metadata

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 v0.2
          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 v0.2
          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 v0.2
          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 v0.2
          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 v0.2
          type: gsm8k
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 53.08
            name: accuracy
pipeline_tag: text-generation

MARS

by Curiosity Technology

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