NeuralBeagle-11B
DPO'd from vicgalle/franken-Beagle-11B, a Beagle-like model upscaled to 11B. It is a frankenmerge model created using mergekit. Then, we applied DPO over a high-quality preference dataset.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 72.06 |
| AI2 Reasoning Challenge (25-Shot) | 73.63 |
| HellaSwag (10-Shot) | 87.86 |
| MMLU (5-Shot) | 63.11 |
| TruthfulQA (0-shot) | 75.92 |
| Winogrande (5-shot) | 82.08 |
| GSM8k (5-shot) | 49.73 |
- Downloads last month
- 73
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Dataset used to train vicgalle/NeuralBeagle-11B-truthy
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard73.630
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard87.860
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard63.110
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard75.920
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard82.080
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard49.730