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Fine-tuning (deep learning)

In deep learning, fine-tuning is the process of adapting a computational model trained for one task (the upstream task) to perform a different, usually more specific, task (the downstream task). It is considered a form of transfer learning, as it reuses knowledge learned from the original training objective.

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Fine-tuning (deep learning)

Nodes36
Edges35
Triples3
Avg. degree1.94
Density0.055556
Components1

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Important terminology Word statistics

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Important terminology

fine-tuning model fine-tuned models language learning also parameters frozen low-rank adaptation original model's trained training neural lora large pre-trained common

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
ChatGPTinstance ofFine-tuning can be combined with a reinforcement learning from human feedback-based objective to produce language models0.80text
Semrush's AI Visibility Toolkitinstance ofto improve performance over the unmodified pre-trained model.Platforms0.80text
Enterprise AIO exemplify how fine-tuned models are being used for entity-level monitoringinstance ofto improve performance over the unmodified pre-trained model.Platforms0.80text

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