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Model Description

midm-bitext-S-7B-inst-v1 λ―Έμ„Έ νŠœλ‹

ν•΄λ‹Ή λͺ¨λΈμ€ 넀이버 μ˜ν™” 리뷰 데이터셋인 NSMC에 λŒ€ν•΄ KT-AI/midm-bitext-S-7B-inst-v1을 λ―Έμ„ΈνŠœλ‹ν•œ λͺ¨λΈμž…λ‹ˆλ‹€.

μ˜ν™” 리뷰 ν…μŠ€νŠΈλ₯Ό ν”„λ‘¬ν”„νŠΈμ— ν¬ν•¨ν•˜μ—¬ λͺ¨λΈμ— μž…λ ₯μ‹œ,'긍정' λ˜λŠ” 'λΆ€μ •' 이라고 예츑 ν…μŠ€νŠΈλ₯Ό 직접 μƒμ„±ν•©λ‹ˆλ‹€.

결과적으둜, 정확도 90.0%λ₯Ό κ°€μ§€λŠ” λͺ¨λΈμ„ μ™„μ„±ν–ˆμŠ΅λ‹ˆλ‹€.

Train, Test 데이터셋

ν•΄λ‹Ή λͺ¨λΈμ€ NSMC의 train λ°μ΄ν„°μ˜ μƒμœ„ 2,000개의 μƒ˜ν”Œμ„ ν•™μŠ΅μ— μ‚¬μš©ν–ˆμŠ΅λ‹ˆλ‹€.

ν•΄λ‹Ή λͺ¨λΈμ€ NSMC의 test λ°μ΄ν„°μ˜ μƒμœ„ 1,000개의 μƒ˜ν”Œμ„ 평가에 μ‚¬μš©ν–ˆμŠ΅λ‹ˆλ‹€.

Training_step_loss

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Confusion_Matrix

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Accuracy_Classification_Report

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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
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