Run_qa.py related query
When we use run_qa.py on bert-base using custom data, will it finetune all the layers(head and body/core) or fine tune only the last layer by freezing other layers?Can we add custom layers and finetune training using run_qa.py, please provide examples.script:main/examples/pytorch/question-answering/run_qa.py
2023-01-05T01:06:38Z
Reviving this thread, please provide answers.
2023-01-06T01:00:50Z
Example command used:python run_qa.py–model_name_or_path bert-base-uncased–dataset_name squad–do_train–do_eval–per_device_train_batch_size 12–learning_rate 3e-5–num_train_epochs 2–max_seq_length 384–doc_stride 128–output_dir /tmp/debug_squad/