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Related Questions
- What are the key differences between masked language modeling and next sentence prediction in pre-training large language models?
- How does the size of the pre-training dataset impact the performance of a large language model on text classification tasks?
- What is the role of contextualized word embeddings in improving the performance of large language models for text classification?
- Can you explain the concept of 'train on a lot of text, fine-tune on a little text' and how it applies to pre-training and fine-tuning large language models?
- How does pre-training on a large corpus of text help a large language model to learn generalizable representations of language?
- What are some common pre-training objectives used in large language models and how do they contribute to their performance on text classification tasks?
- Can you discuss the trade-offs between the size of the pre-training dataset and the computational resources required to train a large language model?
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