Trained on 2 epochs on the EverythingLM-data-V3 dataset.
This model uses the alpaca prompt format:
Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
### Instruction:
Instruction
### Input:
Input
### Response:
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 40.62 |
| AI2 Reasoning Challenge (25-Shot) | 42.75 |
| HellaSwag (10-Shot) | 71.72 |
| MMLU (5-Shot) | 27.16 |
| TruthfulQA (0-shot) | 34.26 |
| Winogrande (5-shot) | 66.30 |
| GSM8k (5-shot) | 1.52 |
- Downloads last month
- 1,149
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 harborwater/open-llama-3b-everythingLM-2048
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard42.750
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard71.720
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard27.160
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard34.260
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard66.300
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard1.520