Prompt sensitivity of transformer variants for text classification
This study investigates the sensitivity of various Transformer model architectures, encoder-only (BERT), decoder-only (GPT-2), and encoder-decoder (T5), in response to various types of prompt modifications on text classification tasks. By leveraging a fine-tuning approach, the models were evaluated...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/181519 |