# Multiple Choice ## Fine-tuning on SWAG ```bash 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 ```