Bart Base Cnn R2 19.4 D35 Hybrid
This is a pruned and optimized BART-base model specifically designed for summarization tasks, retaining 53% of the original model's weights.
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Release Time : 3/2/2022
Model Overview
This model is a summarization model fine-tuned from facebook/bart-base, optimized using the nn_pruning library, and excels on the CNN/DailyMail dataset.
Model Features
Efficient Pruning
Utilizes nn_pruning technology to retain only 35% of linear layer weights, preserving 53% of the original model's weights overall.
Attention Head Optimization
Removed 38 out of 216 attention heads (17.6%), enhancing model efficiency.
High-Performance Summarization
Achieves excellent Rouge scores on the CNN/DailyMail dataset.
Model Capabilities
Text Summarization
Long Text Compression
News Content Condensation
Use Cases
News Processing
News Summarization
Automatically generates concise summaries of news articles
Rouge-1:42.18, Rouge-2:19.44, Rouge-L:39.17
Content Analysis
Long Document Summarization
Extracts and summarizes key information from lengthy documents
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