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---
library_name: peft
base_model: meta-llama/Llama-2-13b-hf
---
## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Framework versions
- PEFT 0.4.0
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_dhmeltzer__Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16)
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | 47.39 |
| ARC (25-shot) | 59.98 |
| HellaSwag (10-shot) | 82.43 |
| MMLU (5-shot) | 55.41 |
| TruthfulQA (0-shot) | 39.9 |
| Winogrande (5-shot) | 76.56 |
| GSM8K (5-shot) | 10.54 |
| DROP (3-shot) | 6.89 |
|