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Related Questions
- What are the key factors that influence the effectiveness of fine-tuning a pre-trained language model on a specific NLP task?
- How does the choice of pre-trained model architecture impact the adaptation process and model performance?
- What are the benefits and limitations of using transfer learning for adapting pre-trained language models to new NLP tasks?
- What role does task-specific data play in the adaptation process, and how does it impact model performance?
- How can the adaptation process be optimized to improve model performance on specific NLP tasks?
- What are some common challenges that arise during the adaptation process, and how can they be addressed?
- Can you provide examples of successful adaptations of pre-trained language models to new NLP tasks, and what factors contributed to their success?
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