Frequent Evaluation Results Summaryįor all the advanced fine-tuning techniques that we’re going to do in this post, we will use the same model and dataset that we have from Transformers, can you rate the complexity of reading passages? These techniques can be used for fine-tuning Transformers such as BERT, ALBERT, RoBERTa, and others. In addition, you may also try to implement some of the advanced training techniques which I’m going to cover in this post. If your Transformer is not performing up to your expectation, what can you do? You may try hyperparameter tuning. The nature and characteristics of the associated data and downstream tasks can also play a part. Such issues are usually more prevalent on large models and small datasets. So, how’s your model doing? Does it manage to achieve reasonably good results? Or does your Transformer model suffer from performance and instability? If yes, the root cause is often difficult to diagnose and determine.
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