readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-large-cnn-finetuned-roundup-2-8
    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-2-8
  
  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: 1.1855
  - Rouge1: 53.552
  - Rouge2: 34.9077
  - Rougel: 38.0158
  - Rougelsum: 50.7179
  - Gen Len: 142.0
  
  ## 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: 8
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | No log        | 1.0   | 167  | 1.2085          | 50.8706 | 32.0069 | 32.9241 | 47.9805   | 142.0    |
  | No log        | 2.0   | 334  | 1.0897          | 53.2218 | 34.1317 | 34.4827 | 50.4795   | 139.4286 |
  | 1.0256        | 3.0   | 501  | 1.0535          | 50.8882 | 30.2514 | 31.5051 | 47.9856   | 141.9048 |
  | 1.0256        | 4.0   | 668  | 1.0515          | 54.9414 | 35.2309 | 36.006  | 52.0331   | 142.0    |
  | 1.0256        | 5.0   | 835  | 1.0829          | 53.0709 | 33.4587 | 36.4223 | 50.1627   | 140.7619 |
  | 0.4579        | 6.0   | 1002 | 1.1310          | 51.5274 | 30.7069 | 32.4146 | 48.8851   | 142.0    |
  | 0.4579        | 7.0   | 1169 | 1.1670          | 52.1536 | 31.7158 | 35.7483 | 49.2678   | 142.0    |
  | 0.4579        | 8.0   | 1336 | 1.1855          | 53.552  | 34.9077 | 38.0158 | 50.7179   | 142.0    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  