Update train_dataset after trainer is initialized
I am trying to fine-tune BERT for token classification under the low-resource setting, where I am aiming to use as few samples as possible (this setting is also calledactive learning). The pipeline is like followingStep 1: Train on initial labeled training setStep 2: Repeat until the annotation budget is reached or performance is good enoughAdd annotated samples to training set based on some criterionRetrain the model on the previously saved checkpointsI have tried the following two implementationsInitializeTrainer(...)every time in Step 2.However, this will cause the model to fine-tune from scratch and therefore seems to be incorrect.Updatetrain_datasetafter theTrainer(...)is initialized.However, from thedoc, it seems that there isnoway to updatetrain_datasetafter the class is initialized.Could someone help me with this (twohowevers). Thank you for any input!