readme: This Model is a fine-tuned version of T-systems [summarization model v1](https://huggingface.co/deutsche-telekom/mt5-small-sum-de-en-v1). 
  
  We used 1000 examples of headline-content pairs from BR24 articles for the fine-tuning process.
  
  Despite the small amount of training data, the tonality of the summarizations has changed significantly. Many of the resulting summaries do sound like a headline.
  
  ## Training
  
  We used the following parameters for training this model:
  
  + base model: deutsche-telekom/mt5-small-sum-de-en-v1
  + source_prefix: "summarize: "
  + batch size: 4
  + max_source_length: 400
  + max_target_length: 35
  + weight_decay: 0.01
  + number of train epochs: 1
  + learning rate: 5e-5
  
  ## License
  
  Since the base model is trained on the MLSUM dataset, this model may not be used for commercial use.
  
  ## Stats
  
  | Model                                   | Rouge1    | Rouge2   | RougeL    | RougeLSum |
  |-----------------------------------------|-----------|----------|-----------|-----------|
  | headlines_test_small_example            | 13.573500 | 3.694700 | 12.560600 | 12.60000  |
  | deutsche-telekom/mt5-small-sum-de-en-v1 | 10.6488   | 2.9313   | 10.0527   | 10.0523   |
  
  