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echarlaix/bart-base-cnn-r2-19.4-d35-hybrid
bart-base-cnn-r2-19.4-d35-hybrid is a summarization model from echarlaix. Use it when you need a shorter version of a longer text. It is set up for transformers. The card lists the license as apache-2.0.
This model was created using the nnpruning python library: the linear layers contains 35% of the original weights.
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From the Hugging Face model README
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).
<div class="graph"><script src="/echarlaix/bart-base-cnn-r2-19.4-d35-hybrid/raw/main/model_card/density_info.js" id="c0afb977-b30c-485d-ac75-afc874392380"></script></div>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%).
| Dataset | Split | # samples |
|---|---|---|
| CNN/DailyMail | train | 287K |
| CNN/DailyMail | eval | 13K |
| Metric | # Value |
|---|---|
| Rouge 1 | 42.18 |
| Rouge 2 | 19.44 |
| Rouge L | 39.17 |