readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-large-cnn-finetuned-roundup-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-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: 1.4519
  - Rouge1: 49.5671
  - Rouge2: 27.0118
  - Rougel: 30.8538
  - Rougelsum: 45.5503
  - Gen Len: 141.75
  
  ## 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   | 132  | 1.3159          | 48.5275 | 28.0817 | 30.6646 | 45.5024   | 142.0   |
  | No log        | 2.0   | 264  | 1.2377          | 47.0791 | 27.4386 | 28.9458 | 44.1536   | 142.0   |
  | No log        | 3.0   | 396  | 1.2474          | 49.3567 | 29.5904 | 30.8029 | 46.6083   | 142.0   |
  | 0.9623        | 4.0   | 528  | 1.2914          | 47.8795 | 27.0611 | 29.8538 | 44.4494   | 142.0   |
  | 0.9623        | 5.0   | 660  | 1.2982          | 49.9921 | 28.4839 | 31.5688 | 46.9734   | 142.0   |
  | 0.9623        | 6.0   | 792  | 1.3521          | 46.7269 | 25.8672 | 29.7325 | 43.8279   | 142.0   |
  | 0.9623        | 7.0   | 924  | 1.4102          | 47.4995 | 26.0066 | 29.4342 | 44.1102   | 141.8   |
  | 0.3734        | 8.0   | 1056 | 1.4519          | 49.5671 | 27.0118 | 30.8538 | 45.5503   | 141.75  |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  