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Related Questions
- What are the key characteristics of BERT models that contribute to their high computational cost in sentiment analysis tasks?
- How does the size and complexity of the BERT model impact its computational requirements during fine-tuning?
- What are the main factors influencing the number of parameters in a BERT model, and how does this affect its computational cost?
- Can you explain the role of attention mechanisms in BERT models and how they contribute to increased computational cost during fine-tuning?
- How does the choice of optimizer and learning rate schedule impact the computational cost of fine-tuning a BERT model for sentiment analysis?
- What are some strategies for reducing the computational cost of fine-tuning BERT models, such as pruning or quantization?
- Can you discuss the impact of batch size and parallelization on the computational cost of fine-tuning a BERT model for sentiment analysis?
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