readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - multi_news
  metrics:
  - rouge
  model-index:
  - name: bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-multi_news
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: multi_news
        type: multi_news
        args: default
      metrics:
      - name: Rouge1
        type: rouge
        value: 38.5318
  ---
  
  <!-- 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. -->
  
  # bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-multi_news
  
  This model is a fine-tuned version of [mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization](https://huggingface.co/mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization) on the multi_news dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.3760
  - Rouge1: 38.5318
  - Rouge2: 12.7285
  - Rougel: 21.4358
  - Rougelsum: 33.4565
  - Gen Len: 128.985
  
  ## 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: 2e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 4.6946        | 0.89  | 400  | 4.5393          | 37.164  | 11.5191 | 20.2519 | 32.1568   | 126.415 |
  | 4.5128        | 1.78  | 800  | 4.4185          | 38.2345 | 12.2053 | 20.954  | 33.0667   | 128.975 |
  | 4.2926        | 2.67  | 1200 | 4.3866          | 38.4475 | 12.6488 | 21.3046 | 33.2768   | 129.0   |
  | 4.231         | 3.56  | 1600 | 4.3808          | 38.7008 | 12.6323 | 21.307  | 33.3693   | 128.955 |
  | 4.125         | 4.44  | 2000 | 4.3760          | 38.5318 | 12.7285 | 21.4358 | 33.4565   | 128.985 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  