We have Llama-3 at home!
Highest PHI-3-Mini MMLU and Winogrande on the board!
The model has been trained on filtered versions of tagged datasets, as well as a few thousand more examples generated with llama-3-70B.
Use Zephyr template with any system message. Default system message should be:
You are a smart, friendly and helpful assistant.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 67.72 |
| AI2 Reasoning Challenge (25-Shot) | 62.29 |
| HellaSwag (10-Shot) | 79.08 |
| MMLU (5-Shot) | 69.44 |
| TruthfulQA (0-shot) | 54.08 |
| Winogrande (5-shot) | 73.40 |
| GSM8k (5-shot) | 68.01 |
- Downloads last month
- 442
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.
Model tree for Ba2han/Llama-Phi-3_DoRA
Datasets used to train Ba2han/Llama-Phi-3_DoRA
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard62.290
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard79.080
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard69.440
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard54.080
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard73.400
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard68.010