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README.md
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## Model description
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## Intended uses & limitations
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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### Training results
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### Framework versions
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## Model description
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Llama-2-7b-chat-hfμ metaμμ κ°λ°ν μ¬μ νμ΅ ν
μ€νΈ μμ± μΈμ΄λͺ¨λΈ μ
λλ€. λ¬Έμμ΄μ μ
λ ₯μΌλ‘ νλ©°, λ¬Έμμ΄μ μμ±ν©λλ€.
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ν΄λΉ λͺ¨λΈ(meta-llama/Llama-2-7b-chat-hf)μ λ² μ΄μ€ λͺ¨λΈλ‘ νμ¬ λ―ΈμΈνλμ μ§ννμμ΅λλ€.
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'Llama-2-7b-chat-hf' is a pre-trained text generation language model developed by Meta. It takes a string as input and generates text.
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We fine-tuned this model based on it(meta-llama/Llama-2-7b-chat-hf).
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## Intended uses & limitations
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nsmc λ°μ΄ν°μ
μ μ¬μ©μκ° μ
λ ₯ν 리뷰 λ¬Έμ₯μ λΆλ₯νλ μμ΄μ νΈμ
λλ€. μ¬μ©μ 리뷰 λ¬Έμ₯μΌλ‘λΆν° 'κΈμ ' λλ 'λΆμ 'μ νλ¨ν©λλ€.
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This agent classifies user-input review sentences from NSMC dataset.
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It determines whether the user review is 'positive' or 'negative' based on the input review sentence.
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## Training and test data
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Training λ° test λ°μ΄ν°λ nsmc λ°μ΄ν° μ
μμ λ‘λ©ν΄ μ¬μ©ν©λλ€. (elvaluation λ°μ΄ν°λ μ¬μ©νμ§ μμ΅λλ€.)
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We load and use training and test data from the NSMC dataset. (We do not use an evaluation data.)
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## Training procedure
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μ¬μ©μμ μν 리뷰 λ¬Έμ₯μ μ
λ ₯μΌλ‘ λ°μ λ¬Έμ₯μ 'κΈμ (1)' λλ 'λΆμ (0)'μΌλ‘ λΆλ₯ν©λλ€.
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Accepts movie review sentences from the user as input and classifies the sentences as 'Positive (1)' or 'Negative (0)'.
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### Training hyperparameters
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The following hyperparameters were used during training:
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### Training results
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- **Binary Confusion Matrix**
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| | TP | TN |
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| PP | 425 | 67 |
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| PN | 66 | 442 |
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- **Accuracy**: 0.894
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### Framework versions
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