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disclaimer
just experimented with the model I had https://huggingface.co./eren23/ogno-monarch-jaskier-merge-7b here with the new preferences dataset of argillia here: https://huggingface.co./datasets/argilla/OpenHermesPreferences
I didn't test the model and the perf wasn't that good when training so use/test it with caution
disclaimer 2
It turns out the model performs well in benchmarks :D
GGUF: https://huggingface.co./eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-GGUF
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 76.45 |
| AI2 Reasoning Challenge (25-Shot) | 73.12 |
| HellaSwag (10-Shot) | 89.09 |
| MMLU (5-Shot) | 64.80 |
| TruthfulQA (0-shot) | 77.45 |
| Winogrande (5-shot) | 84.77 |
| GSM8k (5-shot) | 69.45 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard73.120
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard89.090
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.800
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard77.450
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard84.770
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard69.450