Text Summarization Model Performance Metrics

August 2022 model by ShreySavaliya trained using AutoTrain for text summarization. It reports validation metrics including a Rouge1 score of 43.703 and a RougeLsum score of 38.984.

Use Cases

• Benchmark summarization model performance using Rouge1, Rouge2, and RougeL metrics.
• Analyze the relationship between training loss (2.319) and generation length (141.091 tokens).
• Compare RougeL (23.715) and RougeLsum (38.984) scores for different summary evaluation strategies.

Strengths

• Model trained via AutoTrain, a standardized pipeline.
• Provides 4 distinct Rouge metric scores for evaluation.
• Includes a specific CO2 emissions estimate of 1368.8941 grams.

Limitations

• No dataset size, columns, or sample data provided for underlying training data.
• Model performance metrics (e.g., Rouge1: 43.703) lack a baseline for comparison.
• Last updated in August 2022, potentially using outdated methods or data.

Provenance

Source

Hugging Face, user ShreySavaliya.

Collection Method

Model trained using AutoTrain; underlying data source unknown.

Freshness

Last updated 2022-08-17.