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bart-conversation-summarizer

Summarization
Transformers
PyTorch
bart
text2text-generation
Eval Results
Inference Endpoints
Model card Files Community
1
bart-conversation-summarizer
File size: 4,470 Bytes 
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---
datasets:
- samsum
pipeline_tag: summarization

widget:
  - text: >
      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.      
model-index:
  - name: bart-large-cnn-samsum
    results:
      - task:
          type: summarization
          name: Conversation Summarization
        dataset:
          name: >-
            SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive
            Summarization
          type: samsum
        metrics:
          - type: rogue-1
            value: 54.8764
            name: Validation ROGUE-1
          - type: rogue-2
            value: 29.6869,
            name: Validation ROGUE-2
          - type: rogue-l
            value: 44.9874
            name: Validation ROGUE-L
          - type: loss
            value: 1.47812
            name: loss     


---