---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- cnn_dailymail
model-index:
- name: bart-base-finetuned-summarization-cnn-ver3
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: ccdv/pubmed-summarization
      type: ccdv/pubmed-summarization
      config: section
      split: train
    metrics:
    - type: rouge
      value: 7.4825
      name: ROUGE-1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmMyZDE4ZDFiNjA2ZTBkMTQzMDFiZWFlYjQ4NWI3MWM2MTVmNWM2MmQ2YmYxNGUyMzI1MjcxZWI1OTExYzI4YiIsInZlcnNpb24iOjF9.vehISM8OOOdyb0ZkN8udebOes-YRnUqyV6D6ctQUtCaEXxGjFQQgNLyJJmI7eU28Oum55TRpH82zA4lU9YX6Dg
    - type: rouge
      value: 2.19
      name: ROUGE-2
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOWYxY2ZiNTdjZTRlYTYwM2Q0MmFmMWZkZDJlZTgxODgxMWQ5ZGRiOThkMzNkZjJlNGYyZjMwOTBkNGRlNWYxOCIsInZlcnNpb24iOjF9.VrB5STHbL8ArFnlfloSMzY9oJLRKYmZgoMxrrujRt17hb1H_KKC0l7VG7k1Alja2N2nj8-8WcsVP49fJGS7JAQ
    - type: rouge
      value: 6.2296
      name: ROUGE-L
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiODQ4OTE5MTk0NzI0OTk3MzFhYTNjMmU5ZjA3N2YyOWQ5ODM4MmE5NzE1MzM3NTI3NGM4ODE4Mjk4OGE3YzI1NSIsInZlcnNpb24iOjF9.FJp0BMVhWPMMmME68tHTMNIisB-COWMrfrZAPj9V82lG1fFwxu69bbfqGGONCdpJOZHYazxi5X6aoL2mB3uyAw
    - type: rouge
      value: 6.915
      name: ROUGE-LSUM
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjk2YTY5NTQ5M2YzMmViMDQ3MTllZjM1MjkyZTUwOGJmM2Q3ZDU2ZDU5NDZlMTJmMThjZjM0ODJlZmYzNmU1MiIsInZlcnNpb24iOjF9.CNm77jjHRr9eDgGUhUe9S-KoivV8KcVHIo_4rclEsX8JxbhwXhd06gF7gvlkUyedAqyodS0QEJzQtAiQ7txMAA
    - type: loss
      value: 6.158000469207764
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWFlYWQ1Njk1YTdlNGY3YTgxYzY1Mzc1NzcwYjQyZjkxNTc5ZWViN2FjYjk1MDliMDgzODE1MDgyMzkzMWM3ZSIsInZlcnNpb24iOjF9.eVB-DwOcGg7-y7QG1mNOiU45b1SS39kesQPzU_rzpYknnlFK7Z_AMU9mNj87V2Z2q63VnyIH0uRCM-ijghziAw
    - type: gen_len
      value: 20.0
      name: gen_len
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMWZjMjhjOGUzMWI5N2Q3MWNlNjU2NjM1MDliYWE0YTFlMjM0YTcxYzBhNmVjNjM2YzJlZTdkYWEwMjFlYjY4OSIsInZlcnNpb24iOjF9.7ZPCbgPyUL7MamdNtxIhxditULp3ob6HgYyLMUnsd-xeZ08EPcSwVyM4wgN-REJga4nlNlc94LWzF296K6bnBA
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bart-base-finetuned-summarization-cnn-ver3

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9827
- Bertscore-mean-precision: 0.8811
- Bertscore-mean-recall: 0.8554
- Bertscore-mean-f1: 0.8679
- Bertscore-median-precision: 0.8809
- Bertscore-median-recall: 0.8545
- Bertscore-median-f1: 0.8669

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bertscore-mean-precision | Bertscore-mean-recall | Bertscore-mean-f1 | Bertscore-median-precision | Bertscore-median-recall | Bertscore-median-f1 |
|:-------------:|:-----:|:----:|:---------------:|:------------------------:|:---------------------:|:-----------------:|:--------------------------:|:-----------------------:|:-------------------:|
| 3.632         | 1.0   | 5742 | 2.9827          | 0.8811                   | 0.8554                | 0.8679            | 0.8809                     | 0.8545                  | 0.8669              |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2