readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: BART_reddit_other
    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_reddit_other
  
  This model is a fine-tuned version of [sshleifer/distilbart-xsum-6-6](https://huggingface.co/sshleifer/distilbart-xsum-6-6) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.5792
  - Rouge1: 18.5705
  - Rouge2: 5.0107
  - Rougel: 15.2581
  - Rougelsum: 16.082
  - Gen Len: 19.402
  
  ## 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: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 3.7887        | 1.0   | 1875 | 3.6044          | 18.4668 | 5.182  | 15.359  | 16.169    | 19.341  |
  | 3.3816        | 2.0   | 3750 | 3.5628          | 18.0998 | 4.8937 | 15.0179 | 15.7615   | 17.789  |
  | 3.134         | 3.0   | 5625 | 3.5792          | 18.5705 | 5.0107 | 15.2581 | 16.082    | 19.402  |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  