readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  metrics:
  - rouge
  model-index:
  - name: pegasus-newsroom-cnn_full-adafactor-bs6
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: cnn_dailymail
        type: cnn_dailymail
        args: 3.0.0
      metrics:
      - name: Rouge1
        type: rouge
        value: 44.1026
  ---
  
  <!-- 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. -->
  
  # pegasus-newsroom-cnn_full-adafactor-bs6
  
  This model is a fine-tuned version of [oMateos2020/pegasus-newsroom-cnn_full-adafactor-bs6](https://huggingface.co/oMateos2020/pegasus-newsroom-cnn_full-adafactor-bs6) on the cnn_dailymail dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.8671
  - Rouge1: 44.1026
  - Rouge2: 21.4261
  - Rougel: 31.2033
  - Rougelsum: 41.0324
  - Gen Len: 72.0839
  
  ## 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: 6.4e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 64
  - total_train_batch_size: 256
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 1
  - mixed_precision_training: Native AMP
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 2.9343        | 0.5   | 560  | 2.8733          | 44.1226 | 21.4087 | 31.2431 | 41.0683   | 69.367  |
  | 2.9855        | 1.0   | 1120 | 2.8671          | 44.1026 | 21.4261 | 31.2033 | 41.0324   | 72.0839 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  