miscii-14b-1028
Role-based Instructions
Just parse the following as your system prompt.
Note there is NO special-tokens
here.
system_prompt: str = (
"""<|context_start|>personas
<|user_persona_start|>statement
{user_persona}<|user_persona_end|>
<|assistant_persona_start|>statement
{assistant_persona}<|assistant_persona_end|><|context_end|>""".format(
user_persona="""I am Miscii. # example
<optional: personal statement, e.g. I am the designer of Sthenno.>
<optional: additional statements>""",
assistant_persona="""I am Sthenno. # example
<optional: personal statement, e.g. I speak in Chinese.>
<optional: additional statements>""",
)
)
Training
See Report for miscii-1020 for more details.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 35.05 |
IFEval (0-Shot) | 82.37 |
BBH (3-Shot) | 49.26 |
MATH Lvl 5 (4-Shot) | 6.34 |
GPQA (0-shot) | 14.21 |
MuSR (0-shot) | 12.00 |
MMLU-PRO (5-shot) | 46.14 |
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Model tree for sthenno-com/miscii-14b-1028
Base model
Qwen/Qwen2.5-14B
Finetuned
Qwen/Qwen2.5-14B-Instruct
Datasets used to train sthenno-com/miscii-14b-1028
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard82.370
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard49.260
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard6.340
- acc_norm on GPQA (0-shot)Open LLM Leaderboard14.210
- acc_norm on MuSR (0-shot)Open LLM Leaderboard12.000
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard46.140