Exam D-GAI-F-01 Topic 2 Question 54 Discussion
Actual exam question for EMC's D-GAI-F-01 exam
Question #: 54
Topic #: 2
Question #: 54
Topic #: 2
What is Transfer Learning in the context of Language Model (LLM) customization?
Suggested Answer: C Vote an answer
Transfer learning is a technique in AI where a pre-trained model is adapted for a different but related task.
Here's a detailed explanation:
Transfer Learning:This involves taking a base model that has been pre-trained on a large dataset and fine-tuning it on a smaller, task-specific dataset.
Base Weights:The existing base weights from the pre-trained model are reused and adjusted slightly to fit the new task, which makes the process more efficient than training a model from scratch.
Benefits:This approach leverages the knowledge the model has already acquired, reducing the amount of data and computational resources needed for training on the new task.
References:
Tan, C., Sun, F., Kong, T., Zhang, W., Yang, C., & Liu, C. (2018).A Survey on Deep Transfer Learning. In International Conference on Artificial Neural Networks.
Howard, J., & Ruder, S. (2018). Universal Language Model Fine-tuning for Text Classification.
In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
Here's a detailed explanation:
Transfer Learning:This involves taking a base model that has been pre-trained on a large dataset and fine-tuning it on a smaller, task-specific dataset.
Base Weights:The existing base weights from the pre-trained model are reused and adjusted slightly to fit the new task, which makes the process more efficient than training a model from scratch.
Benefits:This approach leverages the knowledge the model has already acquired, reducing the amount of data and computational resources needed for training on the new task.
References:
Tan, C., Sun, F., Kong, T., Zhang, W., Yang, C., & Liu, C. (2018).A Survey on Deep Transfer Learning. In International Conference on Artificial Neural Networks.
Howard, J., & Ruder, S. (2018). Universal Language Model Fine-tuning for Text Classification.
In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
by Ted at Jul 01, 2025, 01:54 AM
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