hw-llama-2-7B-nsmc

Llama-2 모델을 nsmc 데이터셋을 해결하는 모델이 되도록 미세튜닝하자

• 데이터셋: nsmc
• train은 상위 2000개 이상의 샘플 사용
• test는 상위 1000개 샘플 사용
• 예측에 대한 정확도 분류 지표 측정
• Accuracy 기준 90% 목표

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library_name: peft base_model: meta-llama/Llama-2-7b-chat-hf

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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: False
• bnb_4bit_compute_dtype: bfloat16

Framework versions

• PEFT 0.7.0