---
language:
- tr
- en
license: apache-2.0
library_name: transformers
model-index:
- name: alooowso
  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: 62.97
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=notbdq/alooowso
      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: 84.87
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=notbdq/alooowso
      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: 60.78
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=notbdq/alooowso
      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: 68.18
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=notbdq/alooowso
      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: 77.43
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=notbdq/alooowso
      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: 39.58
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=notbdq/alooowso
      name: Open LLM Leaderboard
---
Fine tuned model of mistral-7b-instruct-v0-2. the dataset used for fine tuning is small and custom dataset for question answering in turkish language made by me. the main duty was to make model more adapted to turkish language.
prompt format : 
```python
[INST]<<SYS>>
{System}
<</SYS>>
{User} [/INST] {Assistant}
```

example in turkish language ;
```python
[INST]<<SYS>>
Aşağıda bir görevi tanımlayan bir talimat bulunmaktadır. İsteği uygun şekilde tamamlayan bir yanıt yazın.
<</SYS>>
python dilinde yılan oyunu için kod verin [/INST] Aşağıda Python dili ile basit bir snake game kodu bulunmaktadır;
import os
import time

# Konfigürasyonlar
WIDTH = 20
HEIGHT = 10
snake_speed = 0.1
snake_size = 3

class Snake:
    def __init__(self):
```
[i cutted output for brevity]
# [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_notbdq__alooowso)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |65.63|
|AI2 Reasoning Challenge (25-Shot)|62.97|
|HellaSwag (10-Shot)              |84.87|
|MMLU (5-Shot)                    |60.78|
|TruthfulQA (0-shot)              |68.18|
|Winogrande (5-shot)              |77.43|
|GSM8k (5-shot)                   |39.58|