Train Bart for Conditional Generation (e.g. Summarization)

[niksqwerty]

@lvwerra

training_args = TrainingArguments(
    output_dir='./models/bart-summarizer',          
    num_train_epochs=1,           
    per_device_train_batch_size=1, 
    per_device_eval_batch_size=1,   
    warmup_steps=500,               
    weight_decay=0.01,              
    logging_dir='./logs',          
)

As per the documentation, labels field is only for “Labels for computing the masked language modeling loss.”, Not specifying ‘labels’ doesn’t provide the loss values, how to compute loss if I want to train only for text summarization?

I am sending encoder_input_ids as paragraph, decoder_input_ids as summary also adding attention_mask_target for both.