| 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 | | |