Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Klasifikim i bazuar në BERT me mbikëqyrje të dobët× | Klasifikim i bazuar në BERT të Stërvitur imët× | |
|---|---|---|
| Fusha | Mësimi i thellë | Mësimi i thellë |
| Familja | Machine learning | Machine learning |
| Viti i origjinës≠ | 2017–2020 | 2019 |
| Krijuesi≠ | Multiple (Ratner et al. for weak supervision framework; Meng et al. for BERT integration) | Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (Google AI) |
| Lloji≠ | Weakly supervised fine-tuning of pre-trained language model | Pre-trained transformer fine-tuned for classification |
| Burimi themelues≠ | Meng, Y., Zhang, Y., Huang, J., Xiong, C., Ji, H., Zhang, C., & Han, J. (2020). Text Classification Using Label Names Only: A Language Model Self-Training Approach. Proceedings of EMNLP 2020, 9006–9017. link ↗ | Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of NAACL-HLT 2019, 4171–4186. DOI ↗ |
| Emërtime të tjera | WS-BERT, BERT with weak supervision, label-efficient BERT classification, noisy-label BERT fine-tuning | BERT fine-tuning, BERT classifier, fine-tuned BERT, BERT sequence classification |
| Të lidhura≠ | 6 | 5 |
| Përmbledhja≠ | Weakly supervised BERT-based classification adapts BERT to text classification tasks when only noisy, heuristic, or programmatically generated labels are available instead of clean human annotations. It combines weak supervision frameworks — such as labeling functions and data programming — with BERT's pre-trained language representations to achieve robust classification without expensive hand-labeling. | Fine-Tuned BERT-based Classification adapts a pre-trained BERT transformer to a specific text classification task by adding a lightweight output layer and continuing gradient-based training on labelled examples. It consistently achieves near-state-of-the-art accuracy on sentiment analysis, topic categorisation, intent detection, and other NLP classification tasks with relatively small labelled datasets. |
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