llama2_nsmc

TODO #1

Llama2 모델의 정확도를 표로 나타내시오.

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• 학습 900번 스텝 수행 시의 정확도는 (402 + 354) / 1000 = 0.756
• 1600 스텝을 시도하고 실패하여 시퀀스 길이를 400으로 줄여 보았는데 예측 정확도가 하락함
• midm 모델은 학습 300번의 스텝을 수행했고, Llama2는 900번의 스텝을 실행하였으나 예측 정확도에는 큰 차이가 없었다.

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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