Model Description
This is a model using the llama2 architecture and only 2 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. | 3.46 |
| IFEval (0-Shot) | 15.82 |
| BBH (3-Shot) | 3.12 |
| MATH Lvl 5 (4-Shot) | 0.00 |
| GPQA (0-shot) | 0.00 |
| MuSR (0-shot) | 0.53 |
| MMLU-PRO (5-shot) | 1.26 |
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Model tree for cpayne1303/smallcp2024
Dataset used to train cpayne1303/smallcp2024
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard15.820
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard3.120
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard0.000
- acc_norm on GPQA (0-shot)Open LLM Leaderboard0.000
- acc_norm on MuSR (0-shot)Open LLM Leaderboard0.530
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard1.260