license: mit language: ko tags: - hate-speech - classification - korean - electra datasets: - jeanlee/kmhas_korean_hate_speech model_name: kcELECTRA-based Korean Hate Speech Classifier
kcELECTRA-based Korean Hate Speech Classifier
μ΄ λͺ¨λΈμ beomi/kcELECTRA-base-v2022λ₯Ό κΈ°λ°μΌλ‘,
jeanlee/kmhas_korean_hate_speech λ°μ΄ν°μ
μ μ¬μ©ν΄ νκ΅μ΄ νμ€ νν λΆλ₯ νμ€ν¬μ λ§μΆ° νμΈνλν λͺ¨λΈμ
λλ€.
π§ λͺ¨λΈ ꡬ쑰
- β Base Model: kcELECTRA-base-v2022 (νκ΅μ΄ μ½νΌμ€ κΈ°λ° μ¬μ νμ΅ ELECTRA)
- β Head: Sequence Classification Head (Binary: νμ€ / λΉνμ€)
- β
Output:
label=1(νμ€),label=0(λΉνμ€)
π λ°μ΄ν°μ μ 보
- μΆμ²: jeanlee/kmhas_korean_hate_speech
- νν: ν μ€νΈ + 8κ°μ§ νμ€ νν λ μ΄λΈ
- μ μ²λ¦¬ λ°©μ:
- λΌλ²¨
8(not_hate_speech)μ0, κ·Έ μΈλ1λ‘ binary classification μ²λ¦¬
- λΌλ²¨
ποΈββοΈ νμΈνλ μ 보
| νλͺ© | κ° |
|---|---|
| Train Epochs | 3 |
| Batch Size | 16 |
| Optimizer | AdamW |
| Learning Rate | 5e-5 |
| Evaluation Metric | Accuracy (μΆκ° κ°λ₯) |
π μ¬μ© μμ (Inference)
from transformers import pipeline
model = pipeline("text-classification", model="jinkyeongk/kcELECTRA-toxic-detector")
text = "λ μ§μ§ λͺ»μκ²Όλ€"
result = model(text)
print(result)
# [{'label': 'LABEL_1', 'score': 0.987}] β νμ€
- Downloads last month
- 308
Inference Providers NEW
This model isn't deployed by any Inference Provider. π Ask for provider support