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--- |
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license: llama3 |
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language: |
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- tr |
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- en |
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base_model: meta-llama/Meta-Llama-3-8B-Instruct |
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model-index: |
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- name: MARS |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge TR |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc |
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value: 46.08 |
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name: accuracy |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU TR |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 47.02 |
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name: accuracy |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA TR |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc |
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name: accuracy |
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value: 49.38 |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande TR |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 53.71 |
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name: accuracy |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k TR |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 53.08 |
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name: accuracy |
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--- |
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<p style="align-self: center"> |
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<img src="MARS-1.0.png" alt="Curiosity MARS model logo" style="border-radius: 1rem"> |
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</p> |
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<div style="display: flex; justify-content: center; align-items: center; flex-direction: column"> |
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<h1 style="font-size: 5em; margin-bottom: 0; padding-bottom: 0;">MARS</h1> |
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<aside>by <a href="https://curiosity.tech">Curiosity Technology</a></aside> |
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</div> |
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MARS is the first iteration of Curiosity Technology models, based on Llama 3 8B. |
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We have trained MARS on in-house Turkish dataset, as well as several open-source datasets and their Turkish |
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translations. |
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It is our intention to release Turkish translations in near future for community to have their go on them. |
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MARS have been tranied for 3 days on 4xA100. |
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## Model Details |
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- **Base Model**: Meta Llama 3 8B Instruct |
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- **Training Dataset**: In-house & Translated Open Source Turkish Datasets |
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- **Training Method**: LoRA Fine Tuning |
