---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: bart-base-finetuned-cnn_dailymail
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: 3.0.0
      split: train
      args: 3.0.0
    metrics:
    - type: rouge
      value: 0.35105989316705805
      name: Rouge1
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: 3.0.0
      split: test
    metrics:
    - type: rouge
      value: 24.5323
      name: ROUGE-1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMTJlYjc4ODQ3ZTE5N2FhOGQ1YjAxZTg4M2RkYzYxZjk0ZTBjNjA2NjQyMDlhYmFjODI4MTAzNjAwNTRkNGVhZCIsInZlcnNpb24iOjF9.gsjbq7FimTwi1pYwEjWYWgC6Slv-ZVSmhxddMTlC7phgOFlYl5G6BRJae-Ml9a6kDJhesaElrD35ToWtndDABw
    - type: rouge
      value: 12.1475
      name: ROUGE-2
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTc2MjZlZjE5NWE1ZDM0NmE2YjU0NDc1YzUxMTMzMGI3YTJlMWFkZjkwM2YyM2Q2NDI5M2U2N2Y2MzZmNGY1MSIsInZlcnNpb24iOjF9.DrRn2tAgmOK_Un-yDKvkfMLm9FbNUxOAvqB_n2ODNuuR1VRRXUxJB8cPzhYElbEm9XRqfE552wHEHvvnCCupDg
    - type: rouge
      value: 20.4203
      name: ROUGE-L
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiN2I0NmYyODFiOGJkMTZhY2Y2NWU4NWU0ZjU0ZTFhZmE4YWU3MTQ3ZjY0NjcyOGNhNzJjODQyYWE1ZGI2MjQ1MiIsInZlcnNpb24iOjF9.087YcSa5OhCOG1Er6BCVybvOAac4SuENP1gQYGpF4LraejxNLHu7kCJT2J5ZRL0w--in_88t22id02BWjUjCAA
    - type: rouge
      value: 23.0696
      name: ROUGE-LSUM
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTk2NWZkZmM1YWM0ODFiOTc4YTUxMmUwMDFlMjJhZWQ1ZGEzYzA4MjM3NTJjMjU4Yjk2NzgwMmZlOTFhZTQ2ZSIsInZlcnNpb24iOjF9.RU2An-d03Zoslimw_8x1jJCKJlrGTXpdv2gXOfQth_6JaQ6i64I_CnfKQZUQ35GqLePtMlSNfeGEgRNEhIYRAw
    - type: loss
      value: 15.141033172607422
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzJjZDk1NGJlZWVhNDY3ODc5NTdiMTEwMDBkYWNkMGIwOGEyZDk0ZDY2NmQ3OTllNDQ0ZTRlNjY4ZTYwNThmZiIsInZlcnNpb24iOjF9.XON0oqXPByyfDSTa92dgvXx26GyamxFFFKkKGyMQpzpRsdWWXDDhQ94Gw4q_MAeBh3rkSgQg3eGQ8ngmsGrtCw
    - type: gen_len
      value: 20.0
      name: gen_len
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmY4ZDA5YjcyNTBkMDI4ZGYyNTc4MDdlNTc5ZDVmYzkyNzEzNzdmNGJjNDc5Mzk5Mjc1N2M1ZmJmNTMzNTdlYSIsInZlcnNpb24iOjF9.UfzSIwX-X4JAZVmEqpDHdLca2OdG1GlWQOVJ7Vdk5CnLen0PyhcDGVSAltiiwZFrL5Jvg850pHWp2h4yNEszCQ
---

<!-- 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-cnn_dailymail

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: 1.5396
- Rouge1: 0.3511
- Rouge2: 0.1925
- Rougel: 0.3086
- Rougelsum: 0.3292

## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.9486        | 1.0   | 35890  | 1.5941          | 0.3498 | 0.1893 | 0.3063 | 0.3272    |
| 1.6706        | 2.0   | 71780  | 1.5601          | 0.3503 | 0.1916 | 0.3079 | 0.3279    |
| 1.4809        | 3.0   | 107670 | 1.5423          | 0.3520 | 0.1923 | 0.3086 | 0.3295    |
| 1.3293        | 4.0   | 143560 | 1.5396          | 0.3511 | 0.1925 | 0.3086 | 0.3292    |


### Framework versions

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