Model Description
This is a model using the llama2 architecture and only 30 million parameters. It is trained on approximately 2 billion tokens of diverse web data from the first 1000000 rows of the uncleaned c4 english dataset.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 3.61 |
| IFEval (0-Shot) | 16.58 |
| BBH (3-Shot) | 2.74 |
| MATH Lvl 5 (4-Shot) | 0.00 |
| GPQA (0-shot) | 0.78 |
| MuSR (0-shot) | 0.46 |
| MMLU-PRO (5-shot) | 1.12 |
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Model tree for cpayne1303/cp2024
Dataset used to train cpayne1303/cp2024
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard16.580
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard2.740
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard0.000
- acc_norm on GPQA (0-shot)Open LLM Leaderboard0.780
- acc_norm on MuSR (0-shot)Open LLM Leaderboard0.460
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard1.120