Datasets:
Update README.md (#4)
Browse files- Update README.md (289ded3958e8ae549eb7ea9ab9effd2da0b0fa8b)
Co-authored-by: Sinisa Stanivuk <Stopwolf@users.noreply.huggingface.co>
README.md
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@@ -35,34 +35,54 @@ We then compare likelihoods of each letter (`A, B, C, D, E`) and calculate the f
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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.
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Exact code for the task
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## Evaluation results
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| Model |Accuracy| |Stderr|
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|GPT-4-0125-preview|0.9199|±|0.002|
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|GPT-4o-2024-05-13|0.9196|±|0.0017|
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|GPT-3.5-turbo-0125|0.8245|±|0.0016|
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### Citation
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```
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@article{oz-eval,
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author = "Stanivuk Siniša & Đorđević Milena",
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title = "
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year = "2024"
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howpublished = {\url{https://huggingface.co/datasets/DjMel/oz-eval}},
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}
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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.
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Exact code for the task can be found as a PR [here](https://github.com/huggingface/lighteval/pull/225).
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You should run the evaluation with the following command (do not forget to add --use_chat_template):
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```
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accelerate launch lighteval/run_evals_accelerate.py \
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--model_args "pretrained={MODEL_NAME},trust_remote_code=True" \
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--use_chat_template \
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--tasks "community|serbian_evals:oz_task|0|0" \
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--custom_tasks "/content/lighteval/community_tasks/oz_evals.py" \
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--output_dir "./evals" \
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--override_batch_size 32
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```
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## Evaluation results
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| Model |Size|Accuracy| |Stderr|
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|-------|---:|-------:|--|-----:|
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|GPT-4-0125-preview|_???_|0.9199|±|0.002|
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|GPT-4o-2024-05-13|_12B_|0.9196|±|0.0017|
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|GPT-3.5-turbo-0125|_20B_|0.8245|±|0.0016|
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|GPT-4o-mini-2024-07-18|_???_|0.7971|±|0.0005|
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|[Mustra-7B-Instruct-v0.2](https://huggingface.co/Stopwolf/Mustra-7B-Instruct-v0.2)|7B|0.7388|± |0.0098|
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|[Tito-7B-slerp](https://huggingface.co/Stopwolf/Tito-7B-slerp)|7B|0.7099|±|0.0101|
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|[Yugo55A-GPT](https://huggingface.co/datatab/Yugo55A-GPT)|7B|0.6889|± |0.0103|
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|[Zamfir-7B-slerp](https://huggingface.co/Stopwolf/Zamfir-7B-slerp)|7B|0.6849|± |0.0104|
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|[Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)|12.2B|0.6839|± |0.0104|
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[Qwen2-7B-instruct](https://huggingface.co/Qwen/Qwen2-7B-Instruct)|7B|0.6730|±|0.0105|
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|[Llama-3-SauerkrautLM-8b-Instruct](https://huggingface.co/VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct)|8B|0.661|± |0.0106|
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|[Yugo60-GPT](https://huggingface.co/datatab/Yugo60-GPT)|7B|0.6411|±|0.0107|
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|[DeepSeek-V2-Lite-Chat](https://huggingface.co/deepseek-ai/DeepSeek-V2-Lite-Chat)|15.7B|0.6047|±|0.0109|
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|[Llama3-70B-Instruct (4bit)](https://huggingface.co/unsloth/llama-3-70b-Instruct-bnb-4bit)|70B|0.5942|±| 0.011|
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|[Hermes-2-Theta-Llama-3-8B](https://huggingface.co/NousResearch/Hermes-2-Theta-Llama-3-8B)|8B|0.5852|±|0.011|
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|[Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)|7B|0.5753|±| 0.011|
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|[openchat-3.6-8b-20240522](https://huggingface.co/openchat/openchat-3.6-8b-20240522)|8B|0.5513|±|0.0111|
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|[Llama3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)|8B|0.5274|±|0.0111|
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|[Starling-7B-beta](https://huggingface.co/Nexusflow/Starling-LM-7B-beta)|7B|0.5244|±|0.0112|
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|[Hermes-2-Pro-Mistral-7B](https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B)|7B|0.5145|±|0.0112|
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|[Qwen2-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2-1.5B-Instruct)|1.5B|0.4506|±|0.0111|
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|[Perucac-7B-slerp](https://huggingface.co/Stopwolf/Perucac-7B-slerp)|7B|0.4247|±|0.011|
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|[Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct)|3.8B|0.3719|±|0.0108|
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|[SambaLingo-Serbian-Chat](https://huggingface.co/sambanovasystems/SambaLingo-Serbian-Chat)|7B|0.2802|±|0.01|
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|[Gemma-2-9B-it](https://huggingface.co/google/gemma-2-9b-it)|9B|0.2193|±|0.0092|
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### Citation
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```
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@article{oz-eval,
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author = "Stanivuk Siniša & Đorđević Milena",
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title = "OZ Eval: Measuring University Level General Knowledge of LLMs in Serbian Language",
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year = "2024"
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howpublished = {\url{https://huggingface.co/datasets/DjMel/oz-eval}},
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}
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