facebook/bart-base model fine-tuned on CNN/DailyMail
This model was created using the nn_pruning python library: the linear layers contains 23% of the original weights.
The model contains 45% of the original weights overall (the embeddings account for a significant part of the model, and they are not pruned by this method).
Fine-Pruning details
This model was fine-tuned from the HuggingFace model. A side-effect of block pruning is that some of the attention heads are completely removed: 61 heads were removed on a total of 216 (28.2%).
Details of the CNN/DailyMail dataset
| Dataset | Split | # samples |
|---|---|---|
| CNN/DailyMail | train | 287K |
| CNN/DailyMail | eval | 13K |
Results
| Metric | # Value |
|---|---|
| Rouge 1 | 41.43 |
| Rouge 2 | 18.72 |
| Rouge L | 38.35 |
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