readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-large-finetuned-large
    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-finetuned-large
  
  This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6397
  - Rouge1: 88.2870
  - Rouge2: 26.4705
  - Rougel: 88.1924
  - Rougelsum: 88.3415
  - Gen Len: 6.0323
  
  ## 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
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | No log        | 1.0   | 121  | 0.8676          | 67.7680 | 19.6386 | 67.5697 | 67.5758   | 6.2774  |
  | No log        | 2.0   | 242  | 0.6661          | 73.6309 | 21.6079 | 73.2496 | 73.5335   | 5.3957  |
  | No log        | 3.0   | 363  | 0.6649          | 82.6362 | 21.4663 | 82.3944 | 82.6107   | 5.6624  |
  | No log        | 4.0   | 484  | 0.6598          | 86.4811 | 25.3580 | 86.1949 | 86.3580   | 5.7914  |
  | 0.5135        | 5.0   | 605  | 0.8032          | 86.0334 | 25.1510 | 85.8895 | 85.9038   | 6.5634  |
  | 0.5135        | 6.0   | 726  | 0.6981          | 88.0139 | 25.6152 | 87.9025 | 87.9932   | 6.3591  |
  | 0.5135        | 7.0   | 847  | 0.6991          | 88.7421 | 25.6469 | 88.5959 | 88.7255   | 6.3376  |
  | 0.5135        | 8.0   | 968  | 0.5995          | 88.9180 | 26.9917 | 88.6984 | 88.8878   | 5.8538  |
  | 0.1613        | 9.0   | 1089 | 0.5973          | 88.5923 | 26.7081 | 88.4593 | 88.6287   | 5.8387  |
  | 0.1613        | 10.0  | 1210 | 0.6397          | 88.2870 | 26.4705 | 88.1924 | 88.3415   | 6.0323  |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  