Their non-commercial research license applies.
I used this script to make the model and used the tokenizer of CausalLM, as suggested in the comments of the script.
https://github.com/hiyouga/LLaMA-Factory/blob/main/tests/llamafy_qwen.py
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 42.94 |
AI2 Reasoning Challenge (25-Shot) | 36.95 |
HellaSwag (10-Shot) | 54.34 |
MMLU (5-Shot) | 44.55 |
TruthfulQA (0-shot) | 43.70 |
Winogrande (5-shot) | 58.88 |
GSM8k (5-shot) | 19.26 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard36.950
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard54.340
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard44.550
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard43.700
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard58.880
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard19.260