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---
library_name: peft
license: llama2
---
## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: True
- load_in_4bit: False
- 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: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
### Framework versions


- PEFT 0.5.0
# [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_Charlie911__vicuna-7b-v1.5-lora-timedial-unit-080091)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 44.44   |
| ARC (25-shot)         | 52.82          |
| HellaSwag (10-shot)   | 76.1    |
| MMLU (5-shot)         | 50.58         |
| TruthfulQA (0-shot)   | 43.4   |
| Winogrande (5-shot)   | 73.72   |
| GSM8K (5-shot)        | 7.66        |
| DROP (3-shot)         | 6.78         |