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--- |
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library_name: peft |
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license: llama2 |
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--- |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: bitsandbytes |
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- load_in_8bit: True |
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- load_in_4bit: False |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: fp4 |
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- bnb_4bit_use_double_quant: False |
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- bnb_4bit_compute_dtype: float32 |
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### Framework versions |
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- PEFT 0.5.0 |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Charlie911__vicuna-7b-v1.5-lora-timedial-unit-080091) |
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| Metric | Value | |
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|-----------------------|---------------------------| |
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| Avg. | 44.44 | |
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| ARC (25-shot) | 52.82 | |
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| HellaSwag (10-shot) | 76.1 | |
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| MMLU (5-shot) | 50.58 | |
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| TruthfulQA (0-shot) | 43.4 | |
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| Winogrande (5-shot) | 73.72 | |
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| GSM8K (5-shot) | 7.66 | |
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| DROP (3-shot) | 6.78 | |
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