Fine-Tuning
Child-Tuning
Introduced by Xu et al. in Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuningChild-Tuning is a fine-tuning technique that updates a subset of parameters (called child network) of large pretrained models via strategically masking out the gradients of the non-child network during the backward process. It decreases the hypothesis space of the model via a task-specific mask applied to the full gradients, helping to effectively adapt the large-scale pretrained model to various tasks and meanwhile aiming to maintain its original generalization ability.
Source: Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning
Papers
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Usage Over Time
Components
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| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
