facebook/bart-base model fine-tuned on CNN/DailyMail
This model was created using the nn_pruning python library: the linear layers contains 35% of the original weights.
The model contains 53% 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 the block pruning is that some of the attention heads are completely removed: 38 heads were removed on a total of 216 (17.6%).
Details of the CNN/DailyMail dataset
| Dataset | Split | # samples |
|---|---|---|
| CNN/DailyMail | train | 287K |
| CNN/DailyMail | eval | 13K |
Results
| Metric | # Value |
|---|---|
| Rouge 1 | 42.18 |
| Rouge 2 | 19.44 |
| Rouge L | 39.17 |
- Downloads last month
- 10
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.