UNA-POLAR-10.7B-InstructMath-v2
Model description
Its a UNA version with DPO over MathPILE Books out of the UNA-SOLAR-10.7B-Instruct-1.0
I used MathPILE OUTSTANDING Dataset of great Mathematic material in order to produce this beautiful model :)
Intended uses & limitations
If your model has inside UNA technology, cite.
Training and evaluation data
UNA-DPO over Attention and MLP's
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2-UNA
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 74.07 |
| AI2 Reasoning Challenge (25-Shot) | 70.73 |
| HellaSwag (10-Shot) | 88.20 |
| MMLU (5-Shot) | 66.03 |
| TruthfulQA (0-shot) | 71.73 |
| Winogrande (5-shot) | 82.95 |
| GSM8k (5-shot) | 64.75 |
- Downloads last month
- 768
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 fblgit/UNA-POLAR-10.7B-InstructMath-v2
Dataset used to train fblgit/UNA-POLAR-10.7B-InstructMath-v2
Spaces using fblgit/UNA-POLAR-10.7B-InstructMath-v2 6
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard70.730
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard88.200
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard66.030
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard71.730
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard82.950
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard64.750