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Related Questions
- What are the key differences between pre-training and fine-tuning in the context of large language models?
- How does pre-training on a large corpus of text data enable large language models to perform well on downstream tasks such as sentiment analysis?
- Can you provide examples of pre-training objectives and tasks that improve a large language model's performance on sentiment analysis?
- What are some common pitfalls or challenges associated with pre-training and fine-tuning large language models for sentiment analysis?
- How can pre-training and fine-tuning be used in conjunction with other techniques, such as transfer learning, for improved performance on sentiment analysis?
- What are some key hyperparameters and settings that need to be adjusted during fine-tuning to optimize a large language model's performance on sentiment analysis?
- Can you discuss the trade-offs between the size and complexity of pre-trained models and their performance on sentiment analysis tasks?
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