readme: ---
  license: apache-2.0
  ---
  T5-base fine-tuned on CNN/DM Summarization dataset.
  
  
  Training args:
  ```
  {
              "learning_rate": 0.0001,
              "logging_steps": 5000,
              "lr_scheduler_type": "cosine",
              "num_train_epochs": 2,
              "per_device_train_batch_size": 16, # total batch size of 48
              "save_total_limit": 1,
              "weight_decay": 0.1
  }
  ```
  
  Generation kwargs: 
  ```
  {
              "do_sample": true,
              "max_new_tokens": 100,
              "min_length": 50,
              "temperature": 0.7,
              "top_k": 0
   },
   ````
  
  Pre-processing: Append prompt with prefix "Summarize: "
  Post-processing: None
  
  Test split metrics:
  
  ```
  {"lexical/meteor": 0.30857827917561603, 
  "lexical/rouge_rouge1": 0.41099971702474514, 
  "lexical/rouge_rouge2": 0.17676173608661166, 
  "lexical/rouge_rougeL": 0.2759112075051335, 
  "lexical/rouge_rougeLsum": 0.34316108028094616, 
  "lexical/bleu": 0.10747816852428271, 
  "semantic/bert_score": 0.8760301497472277}
  ```