T5 Small German
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T5 Small German
Developed by Shahm
A German abstract generation model fine-tuned based on the T5-small architecture, trained for 7 epochs on the mlsum German dataset with a Rouge1 score of 42.38
Downloads 108
Release Time : 3/2/2022
Model Overview
This model is a Transformer optimized for automatic abstract generation tasks in German, suitable for extracting key information from German news and other texts to generate concise summaries.
Model Features
German Optimization
Fine-tuned specifically for German text characteristics, handling German grammatical structures and vocabulary features more accurately
Efficient Summarization
Generates summaries with an average length of 47.8 tokens, achieving high compression while maintaining information integrity
Multi-dimensional Evaluation
Comprehensively evaluates summary quality through Rouge1/2/L/Lsum metrics
Model Capabilities
German Text Comprehension
Automatic Abstract Generation
Text Compression
Key Information Extraction
Use Cases
News Processing
News Brief Generation
Automatically compresses German news articles into concise bullet-point summaries
Rouge1 score of 42.38, retaining the main information of the original text
Content Analysis
Long Document Summarization
Generates executive summaries for German technical documents or reports
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