DPO Finetuned Kukedlc/NeuTrixOmniBe-7B-model-remix using argilla/OpenHermes2.5-dpo-binarized-alpha
argilla dpo binarized pairs is a dataset built on top of: https://huggingface.co/datasets/teknium/OpenHermes-2.5 using https://github.com/argilla-io/distilabel if interested.
Thx for the great data sources.
GGUF: https://huggingface.co/eren23/dpo-binarized-NeutrixOmnibe-7B-GGUF
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 76.31 |
| AI2 Reasoning Challenge (25-Shot) | 72.78 |
| HellaSwag (10-Shot) | 89.05 |
| MMLU (5-Shot) | 64.60 |
| TruthfulQA (0-shot) | 76.90 |
| Winogrande (5-shot) | 85.08 |
| GSM8k (5-shot) | 69.45 |
- Downloads last month
- 88
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for eren23/dpo-binarized-NeutrixOmnibe-7B
Dataset used to train eren23/dpo-binarized-NeutrixOmnibe-7B
Spaces using eren23/dpo-binarized-NeutrixOmnibe-7B 6
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard72.780
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard89.050
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.600
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard76.900
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard85.080
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard69.450