README.md

---
language:
- sr
license: apache-2.0
task_categories:
- question-answering
dataset_info:
  features:
  - name: index
    dtype: int64
  - name: questions
    dtype: string
  - name: options
    sequence: string
  - name: answer
    dtype: string
  - name: answer_index
    dtype: int64
  splits:
  - name: test
    num_bytes: 200846
    num_examples: 1003
  download_size: 139630
  dataset_size: 200846
configs:
- config_name: default
  data_files:
  - split: test
    path: data/oz-eval-*
---

# OZ Eval
![image/png](https://cdn-uploads.huggingface.co/production/uploads/62d01cf580c9d4ceb20254bb/Ft9w9DNRN_1bzuQC9XNSG.png)

## Dataset Description
OZ Eval (_sr._ Opšte Znanje Evaluacija) dataset was created for the purposes of evaluating General Knowledge of LLM models in Serbian language. 
Data consists of 1k+ high-quality questions and answers which were used as part of entry exams at the Faculty of Philosophy and Faculty of Organizational Sciences, University of Belgrade.
The exams test the General Knowledge of students and were used in the enrollment periods from 2003 to 2024. 

This is a joint work with [@Stopwolf](https://huggingface.co/Stopwolf)!


## Evaluation process
Models are evaluated by the following principle using HuggingFace's library `lighteval`. We supply the model with the following template:
```
Pitanje: {question}

Ponuđeni odgovori:
A. {option_a}
B. {option_b}
C. {option_c}
D. {option_d}
E. {option_e}

Krajnji odgovor:
```
We then compare likelihoods of each letter (`A, B, C, D, E`) and calculate the final accuracy. All evaluations are ran in a 0-shot manner using a **chat template**.

GPT-like models were evaluated by taking top 20 probabilities of the first output token, which were further filtered for letters `A` to `E`. Letter with the highest probability was taken as a final answer. 

Exact code for the task can be found [here](https://github.com/Stopwolf/lighteval/blob/oz-eval/community_tasks/oz_evals.py).

You should run the evaluation with the following command (do not forget to add --use_chat_template):
```
accelerate launch lighteval/run_evals_accelerate.py \
    --model_args "pretrained={MODEL_NAME},trust_remote_code=True" \
    --use_chat_template \
    --tasks "community|serbian_evals:oz_task|0|0" \
    --custom_tasks "/content/lighteval/community_tasks/oz_evals.py" \
    --output_dir "./evals" \
    --override_batch_size 32
```

## Evaluation results
| Model |Size|Accuracy|  |Stderr|
|-------|---:|-------:|--|-----:|
|GPT-4-0125-preview|_???_|0.9199|±|0.002|
|GPT-4o-2024-05-13|_???_|0.9196|±|0.0017|
|GPT-3.5-turbo-0125|_???_|0.8245|±|0.0016|
|[Llama3.1-70B-Instruct \[4bit\]](https://huggingface.co/unsloth/Meta-Llama-3.1-70B-bnb-4bit)|70B|0.8185|±| 0.0122|
|GPT-4o-mini-2024-07-18|_???_|0.7971|±|0.0005|
|[Mustra-7B-Instruct-v0.2](https://huggingface.co/Stopwolf/Mustra-7B-Instruct-v0.2)|7B|0.7388|±  |0.0098|
|[Tito-7B-slerp](https://huggingface.co/Stopwolf/Tito-7B-slerp)|7B|0.7099|±|0.0101|
|[Yugo55A-GPT](https://huggingface.co/datatab/Yugo55A-GPT)|7B|0.6889|±  |0.0103|
|[Zamfir-7B-slerp](https://huggingface.co/Stopwolf/Zamfir-7B-slerp)|7B|0.6849|±  |0.0104|
|[Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)|12.2B|0.6839|±  |0.0104|
|[Llama-3.1-SauerkrautLM-8b-Instruct](https://huggingface.co/VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct)|8B|0.679|±|0.0147|
[Qwen2-7B-instruct](https://huggingface.co/Qwen/Qwen2-7B-Instruct)|7B|0.6730|±|0.0105|
|[Llama-3-SauerkrautLM-8b-Instruct](https://huggingface.co/VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct)|8B|0.661|±  |0.0106|
|[Yugo60-GPT](https://huggingface.co/datatab/Yugo60-GPT)|7B|0.6411|±|0.0107|
|[DeepSeek-V2-Lite-Chat](https://huggingface.co/deepseek-ai/DeepSeek-V2-Lite-Chat)|15.7B|0.6047|±|0.0109|
|[Llama3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct)|8B|0.5972|±| 0.0155|
|[Llama3-70B-Instruct \[4bit\]](https://huggingface.co/unsloth/llama-3-70b-Instruct-bnb-4bit)|70B|0.5942|±| 0.011|
|[Hermes-3-Theta-Llama-3-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B)|8B|0.5932|±|0.0155|
|[Hermes-2-Theta-Llama-3-8B](https://huggingface.co/NousResearch/Hermes-2-Theta-Llama-3-8B)|8B|0.5852|±|0.011|
|[Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)|7B|0.5753|±| 0.011|
|[openchat-3.6-8b-20240522](https://huggingface.co/openchat/openchat-3.6-8b-20240522)|8B|0.5513|±|0.0111|
|[Llama3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)|8B|0.5274|±|0.0111|
|[Starling-7B-beta](https://huggingface.co/Nexusflow/Starling-LM-7B-beta)|7B|0.5244|±|0.0112|
|[Hermes-2-Pro-Mistral-7B](https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B)|7B|0.5145|±|0.0112|
|[Qwen2-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2-1.5B-Instruct)|1.5B|0.4506|±|0.0111|
|[Perucac-7B-slerp](https://huggingface.co/Stopwolf/Perucac-7B-slerp)|7B|0.4247|±|0.011|
|[Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct)|3.8B|0.3719|±|0.0108|
|[SambaLingo-Serbian-Chat](https://huggingface.co/sambanovasystems/SambaLingo-Serbian-Chat)|7B|0.2802|±|0.01|
|[Gemma-2-9B-it](https://huggingface.co/google/gemma-2-9b-it)|9B|0.2193|±|0.0092|
|[Gemma-2-2B-it](https://huggingface.co/google/gemma-2-2b-it)|2.6B|0.1715|±|0.0084|


### Citation
```
@article{oz-eval,
  author    = "Stanivuk Siniša & Đorđević Milena",
  title     = "OZ Eval: Measuring General Knowledge Skill at University Level of LLMs in Serbian Language",
  year      = "2024"
  howpublished = {\url{https://huggingface.co/datasets/DjMel/oz-eval}},
}
```