ChatGPT Paraphraser on T5-base
| Property | Value |
|---|---|
| License | OpenRAIL |
| Architecture | T5-base |
| Language | English |
| Framework | PyTorch/Transformers |
What is chatgpt_paraphraser_on_T5_base?
This is a specialized paraphrasing model built on the T5-base architecture, trained using a unique dataset of ChatGPT-generated paraphrases. The model combines data from multiple high-quality sources, including Quora paraphrase questions, SQUAD 2.0, and CNN news dataset, to create a robust paraphrasing system that matches ChatGPT's capabilities.
Implementation Details
The model employs advanced generation parameters including beam search with 5 beams and groups, maintaining diversity through a penalty of 3.01 and a repetition penalty of 10.01. It operates at a temperature of 0.7 for balanced creativity and coherence, with a maximum sequence length of 128 tokens.
- Transfer learning approach utilizing T5-base architecture
- Trained for 5 epochs with a batch size of 64
- Learning rate of 5e-5 with Adam optimizer (betas=(0.9, 0.999))
- 196,465 training batches for comprehensive learning
Core Capabilities
- Generation of multiple diverse paraphrases for a given input
- Handling of both questions and statements
- Maintenance of semantic meaning while varying expression
- Support for complex sentence structures
- Context-aware reformulation of text
Frequently Asked Questions
Q: What makes this model unique?
This model stands out due to its training on ChatGPT-generated paraphrases, combining the power of T5 architecture with modern language modeling capabilities. The careful tuning of generation parameters ensures diverse and high-quality outputs while maintaining semantic accuracy.
Q: What are the recommended use cases?
The model excels in content rephrasing, question reformulation, and text variation generation. It's particularly useful for content creators, SEO specialists, and applications requiring multiple ways to express the same information.
