readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-large-cnn-finetuned-roundup-2-4
    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. -->
  
  # bart-large-cnn-finetuned-roundup-2-4
  
  This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0908
  - Rouge1: 51.9961
  - Rouge2: 32.3963
  - Rougel: 32.1774
  - Rougelsum: 50.1033
  - Gen Len: 141.0
  
  ## 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: 2
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | No log        | 1.0   | 167  | 1.2152          | 52.234  | 33.1104 | 33.308  | 49.5516   | 142.0    |
  | No log        | 2.0   | 334  | 1.1054          | 52.7096 | 33.4698 | 33.9595 | 49.8736   | 140.3333 |
  | 1.0437        | 3.0   | 501  | 1.0796          | 51.699  | 32.4255 | 34.0294 | 49.5276   | 141.7143 |
  | 1.0437        | 4.0   | 668  | 1.0908          | 51.9961 | 32.3963 | 32.1774 | 50.1033   | 141.0    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  