Chat Summarizer

🚀 Bart-large-cnn-samsum for Conversation Summarization

This project focuses on conversation summarization, using the bart-large-cnn-samsum model trained on the samsum dataset. It aims to provide accurate summaries of conversations, which is useful in various communication scenarios.

🚀 Quick Start

The model is designed for conversation summarization. You can use it to quickly generate summaries of dialogues like the following example.

💻 Usage Examples

Basic Usage

The following is a conversation example:

Laurie: So, what are your plans for this weekend?

Christie: I don’t know. Do you want to get together or something?

Sarah: How about going to see a movie? Cinemax 26 on Carson Boulevard is showing Enchanted.
Laurie: That sounds like a good idea. Maybe we should go out to eat beforehand.

Sarah: It is fine with me. Where do you want to meet?

Christie: Let’s meet at Summer Pizza House. I have not gone there for a long time.

Laurie: Good idea again. I heard they just came up with a new pizza. It should be good because Summer Pizza House always has the best pizza in town.

Sarah: When should we meet?

Christie: Well, the movie is shown at 2:00PM, 4:00PM, 6:00PM and 8:00PM.

Laurie: Why don’t we go to the 2:00PM show? We can meet at Summer Pizza House at noon. That will give us plenty of time to enjoy our pizza.

Sarah: My cousin Karen is in town. Can I bring her along? I hate to leave her home alone.

Christie: Karen is in town? Yes, bring her along. Laurie, you remember Karen? We met her at Sara’s high school graduation party two years ago.

Laurie: I do not quite remember her. What does she look like?

Sarah: She has blond hair, she is kind of slender, and she is about your height.

Laurie: She wears eyeglasses, right?

Sarah: Yes, and she was playing the piano off and on during the party.

Laurie: I remember her now. Yes, do bring her along Sara. She is such a nice person, and funny too.

Sarah: She will be happy to meet both of you again.

Christie: What is she doing these days?

Sarah: She graduated last June, and she will start her teaching career next week when the new school term begins.

Laurie: What grade is she going to teach?

Sarah: She will teach kindergarten. She loves working with kids, and she always has such a good rapport with them

Christie: Kindergarten? She must be a very patient person. I always think kindergarten is the most difficult class to teach. Most of the kids have never been to school, and they have
e never been away from mommy for long.

Sarah:  I think Karen will do fine. She knows how to handle young children

Laurie: I think the first few weeks will be tough. However, once the routine is set, it should not be too difficult to teach kindergarten.

Christie: You are right. The kids might even look forward to going to school since they have so many friends to play with.

Sarah: There are so many new things for them to do at school too. They do a lot of crafts in kindergarten. I am always amazed by the things kindergarten teachers do. 

Laurie: Yes, I have seen my niece come home with so many neat stuff.

Christie: Maybe we can ask Karen to show us some of the things that we can do for this Halloween.

Laurie: Maybe we can stop by the craft store after the movie. What do you think, Sara?

Sarah: I will talk to her. I think she will like that. It will help her with school projects when Halloween comes.

Christie: Michael’s is a good store for crafts. It always carries a variety of things, and you can find almost anything there.

Laurie: There is a Michaels store not far away from Cinemax 26. I believe it is just around the corner, on Pioneer Avenue. We can even walk over there.

Sarah: So, we plan to meet for pizza at noon, go to the movies at two, and shop at Michael’s afterward. Right?

Laurie and Christie: Yes.      

The model can summarize this conversation to extract the key information.

📚 Documentation

Model Information

Evaluation Metrics

The model has been evaluated on the samsum dataset using the following metrics: