Fine-tuning Resume Summary Generation Model with DistilBART-cnn-12-6 - Open-source and Practical, Generating High-quality Resume Summaries

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Distilbart Cnn 12 6 Finetuned Resume Summarizer

Developed by Ameer05

A resume summary generation model fine-tuned based on distilbart-cnn-12-6, performing well on ROUGE metrics

Text Generation

Transformers

#Resume Summary Generation #High ROUGE Score #Lightweight BART

Downloads 19

Release Time : 3/21/2022

Model Overview

This model is a fine-tuned text summarization model specifically designed to extract key information from resume texts and generate summaries. Based on the DistilBART architecture, it provides good summarization capabilities while maintaining a lightweight model.

Model Features

Efficient Summary Generation

Based on the DistilBART architecture, it provides efficient summarization capabilities while maintaining a lightweight model.

Resume Domain Optimization

Specifically fine-tuned for resume texts, it better understands key information such as professional experience and educational background.

Multi-dimensional Evaluation

Comprehensively evaluated using multiple metrics including ROUGE-1, ROUGE-2, and ROUGE-L.

Model Capabilities

Text Summarization Generation

Key Information Extraction

Resume Content Condensation

Use Cases

Human Resources

Rapid Resume Screening

Automatically generates resume summaries for recruiters to improve screening efficiency

ROUGE-1 score of 52.58, effectively extracting key information from resumes

Career Services

Resume Optimization Suggestions

Analyzes resume content completeness through summary generation

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
No log	0.91	5	3.2243	42.8593	24.8652	34.1789	41.406
No log	1.91	10	2.6948	48.8571	28.6711	39.2648	46.188
No log	2.91	15	2.4665	50.6085	30.4034	39.7406	48.5449
No log	3.91	20	2.3329	52.2357	32.3398	41.574	49.4316
3.6611	4.91	25	2.2362	52.0134	33.1612	41.3103	50.255
3.6611	5.91	30	2.1833	51.5434	32.7045	40.5683	49.4238
3.6611	6.91	35	2.1462	53.5144	35.4518	42.8615	51.4053
3.6611	7.91	40	2.1518	52.0985	33.6754	41.5936	50.5159
2.0326	8.91	45	2.1075	53.1401	34.9721	42.2973	51.8454
2.0326	9.91	50	2.1123	52.5826	34.3861	41.8525	51.0015

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Distilbart Cnn 12 6 Finetuned Resume Summarizer

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 distilbart-cnn-12-6-finetuned-resume-summarizer

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

🔧 Technical Details

Training procedure

Training hyperparameters

Training results

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