This is the command that I am using
train_distilbart_seq2seq --output_dir /tmp/path/to/dir/ \
                         --model_name facebook/bart-large-xsum \
                         --tokenizer_name facebook/bart-large-xsum \
                         --task summarization \
                         --dataset_name xsum \
                         --learning_rate 3e-4 \ (taken from the [example script](https://github.com/huggingface/transformers/tree/master/examples/research_projects/seq2seq-distillation))
                         --use_kd_loss True \
                         --alpha_data 1.0 \
                         --alpha_logits 0.8 \
                         --alpha_hidden 3.0 \
                         --max_source_length 1024 \
                         --max_target_length 256 \
                         --do_train \
                         --do_eval \
                         --do_predict \
                         --num_beams 6 \
                         --num_train_epochs 5 \
                         --evaluation_strategy steps \
                         --save_total_limit 5 \
                         --load_best_model_at_end \
                         --predict_with_generate

I did not specify min_length, max_length, and length_penalty as I let them take the values from the teacher model (min_length=11, max_length=62, which match the config in the model hub, I will need to double-check length_penalty). Other than that, please let me know if there’s anything wrong with my command. Thank you!