readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-base-finetuned-kaggglenews-batch8-epochs10
    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-base-finetuned-kaggglenews-batch8-epochs10
  
  This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.5763
  - Rouge1: 28.693
  - Rouge2: 16.666
  - Rougel: 24.2361
  - Rougelsum: 26.0289
  - Gen Len: 20.0
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | No log        | 1.0   | 495  | 1.6043          | 27.8611 | 15.8713 | 23.8365 | 25.378    | 20.0    |
  | 1.9054        | 2.0   | 990  | 1.5613          | 28.2715 | 16.3724 | 24.3212 | 25.8499   | 20.0    |
  | 1.651         | 3.0   | 1485 | 1.5394          | 28.6282 | 16.2976 | 24.2336 | 25.9434   | 20.0    |
  | 1.4955        | 4.0   | 1980 | 1.5438          | 28.9266 | 16.7257 | 24.61   | 26.443    | 20.0    |
  | 1.4034        | 5.0   | 2475 | 1.5449          | 28.2296 | 16.1292 | 23.9698 | 25.651    | 20.0    |
  | 1.3077        | 6.0   | 2970 | 1.5642          | 28.4486 | 16.3833 | 24.1629 | 26.0013   | 20.0    |
  | 1.2505        | 7.0   | 3465 | 1.5566          | 28.5469 | 16.5374 | 24.2966 | 25.962    | 20.0    |
  | 1.2027        | 8.0   | 3960 | 1.5730          | 28.7278 | 16.6442 | 24.2531 | 26.1171   | 20.0    |
  | 1.1571        | 9.0   | 4455 | 1.5690          | 28.7736 | 16.7491 | 24.3066 | 26.1439   | 20.0    |
  | 1.1237        | 10.0  | 4950 | 1.5763          | 28.693  | 16.666  | 24.2361 | 26.0289   | 20.0    |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0+cu102
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  