readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bert-small2bert-small-finetuned-cnn_daily_mail-summarization-newsroom-filtered
    results: []
  ---
  
  <!-- 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-newsroom-filtered
  
  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 an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.5413
  - Rouge1: 32.3232
  - Rouge2: 20.9203
  - Rougel: 27.232
  - Rougelsum: 29.345
  - Gen Len: 72.2217
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 3.796         | 0.89  | 405  | 3.6945          | 29.7168 | 17.6705 | 24.4204 | 26.484    | 69.6847 |
  | 3.6426        | 1.78  | 810  | 3.5532          | 32.3051 | 20.8789 | 27.1724 | 29.384    | 72.3695 |
  | 3.2645        | 2.66  | 1215 | 3.5437          | 32.2016 | 20.758  | 27.083  | 29.0954   | 73.3892 |
  | 3.1719        | 3.55  | 1620 | 3.5377          | 32.5493 | 21.083  | 27.0881 | 29.4691   | 71.5222 |
  | 2.9763        | 4.44  | 2025 | 3.5413          | 32.3232 | 20.9203 | 27.232  | 29.345    | 72.2217 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  