Papers by Toshiki Kuramoto

1 papers
Predicting Fine-tuned Performance on Larger Datasets Before Creating Them (2025.coling-industry)

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Challenge: a method to estimate the performance of pretrained models fine-tuned with a larger dataset is proposed . a recent study found that fine-timing PMs with the small amount of data does not always result in ideal performance.
Approach: They propose a method to estimate the performance of pretrained models fine-tuned with a larger dataset from the result with fewer epochs.
Outcome: The proposed method can help resource-limited companies develop machine-learning models . it shows that when a model is fine-tuned with a larger dataset, its classification performance increases .

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