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license: mit |
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language: |
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- en |
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metrics: |
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- bertscore |
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base_model: |
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- LLM-PBE/Llama3.1-8b-instruct-LLMPC-Blue-Team |
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--- |
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Model Card: LLM-PBE-FineTuned-FakeData |
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Model Details |
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- Model Name: LLM-PBE-FineTuned-FakeData |
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- Creator: SanjanaCodes |
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- Language: English |
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Description |
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This model is a fine-tuned LLM trained on synthetic (fake) data for research purposes. It’s designed to help understand model behavior and the impact of fine-tuning with controlled, artificial datasets. This model should not be used for real-world applications due to its limited real-world relevance. |
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Intended Use |
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- Research: Fine-tuning experiments, synthetic data evaluation. |
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- Educational: Suitable for controlled testing and benchmarking. |
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Limitations |
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- Performance: May lack contextual accuracy and depth outside synthetic data contexts. |
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- Generalization: Best suited for synthetic data scenarios rather than practical applications. |
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Acknowledgments |
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Trained at NYU Tandon DICE Lab under Professor Chinmay Hegde & Niv Cohen |
