23 июн. 2021 г. · Broadly speaking, to reduce overfitting, you can: increase regularization; reduce model complexity; perform early stopping ...

4 июл. 2021 г. · The model overfits badly. The training accuracy goes up to ~99% while the validation accuracy barely crosses 50% mark.

5 апр. 2023 г. · I am currently attempting to build a named entity recognition system for the Moroccan Dialect using BERT+ BiGRU+Softmax architecture.

7 нояб. 2019 г. · To clarify, your loss function is always calculated on Training set, and thus overfitting may happen on the training set.

2 сент. 2021 г. · There are multiple approaches to fine-tune BERT for the target tasks. Note that the BERT base model has been pre-trained only for two tasks as in the original ...

21 дек. 2021 г. · I think you might have the problem of overfitting, i.e. your model is focussing on too specific features for it to generalize well.

26 июл. 2020 г. · Further training often translates to overfitting to your data and forgetting the pre-trained weights (see catastrophic forgetting). In my ...

26 июл. 2021 г. · There are two ways to train a BERT-based classification model. Research has shown that finetuning delivers slightly better results than when using BERT as ...

11 июл. 2022 г. · I am trying to interpret these learning curves. These seem to overfit after the 1st epoch. I have built a model using TensorFlow and the BERT transformer.

27 мая 2021 г. · Short answer to the question: yes, they are overfitting. Most of the important NLP data sets are not actually well-crafted enough to test what they claim to ...