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* Base move * Examples reorganization * Update references * Put back test data * Move conftest * More fixes * Move test data to test fixtures * Update path * Apply suggestions from code review Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * Address review comments and clean Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
1.1 KiB
1.1 KiB
Multiple Choice
Fine-tuning on SWAG
export SWAG_DIR=/path/to/swag_data_dir
python ./examples/multiple-choice/run_tf_multiple_choice.py \
--task_name swag \
--model_name_or_path bert-base-cased \
--do_train \
--do_eval \
--data_dir $SWAG_DIR \
--learning_rate 5e-5 \
--num_train_epochs 3 \
--max_seq_length 80 \
--output_dir models_bert/swag_base \
--per_gpu_eval_batch_size=16 \
--per_device_train_batch_size=16 \
--logging-dir logs \
--gradient_accumulation_steps 2 \
--overwrite_output