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Model Details
Model Description
이 모델은 NSMC(Naver Sentiment Movie Corpus) 데이터에 대한 meta-llama/Llama-2-7b-chat-hf 모델의 미세 튜닝을 기반으로 합니다.
목표
- 영화 리뷰 텍스트를 프롬프트에 포함하여 모델에 입력하면 '긍정' 또는 '부정'이라고 예측하는 텍스트를 직접 생성하는 것입니다.
요건
- NSMC의 train 스플릿 앞쪽 2,000개 이상의 샘플을 학습에 사용했습니다.
- 테스트는 test 스플릿 앞쪽 1,000개의 샘플만을 사용하여 측정했습니다.
Accuracy : 90.10%
| TP | TN |
|---|
| PP | 458 | 50.000 |
| PN | 49 | 443.000 |
| Accuracy | - | 0.901 |
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Training Details
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Lacoste et al. (2019).
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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
