Papers by Sorelle Friedler
Energy and Carbon Considerations of Fine-Tuning BERT (2023.findings-emnlp)
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| Challenge: | Existing work quantifying energy costs and associated carbon emissions has focused on pretraining and fine-tuning. |
| Approach: | They perform an empirical study to quantify the energy requirements of language model fine-tuning in the context of pretraining and inference. |
| Outcome: | The proposed model fine-tuning energy and carbon footprints are compared with pre-training and inference energy requirements and outline recommendations for NLP researchers and practitioners. |