I have my own corpus that I have made and that I am working with (10k observations) of small and moderate length documents. The summaries I have are very small, no greater than 18 words, the results are below.
##    rouge1  rouge2  rougeL
## P   0.517   0.309   0.496
## R   0.537   0.321   0.514
## F   0.523   0.313   0.502

I am going to try the </s> as recommended above. I suppose I am doing something similar in that I:

I add add summarize to the main text: df['body'] = 'summarize: ' + df['body']

I add a pad token to the summary text first position: df['summary'] = df['summary'].apply(lambda x: '<pad>' + x)


I guess the question is though, do we need to do it anymore? This post suggests an update, but I am not sure if its in the nightly release yet.

  
      github.com/huggingface/transformers
  
  
    
  
	  
  

  
    
      Truncated Outputs by t5 fine-tuned models 12
    

    
      
        opened 
        
          
        
        Jul 10, 2020
      
      


      
        
          
          tromedlov22
        
      
    
  



  I fine-tuned t5-small over CNN/DM dataset using the finetune_t5.sh script. The outputs produced by the saved fine-tuned model is okayish but...



    t5