readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: BART_reddit_gaming
    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_gaming
  
  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: 3.7373
  - Rouge1: 18.1202
  - Rouge2: 4.6045
  - Rougel: 15.1273
  - Rougelsum: 15.7601
  - Gen Len: 18.208
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 3.864         | 1.0   | 1875 | 3.7752          | 17.3754 | 4.51   | 14.6763 | 15.22     | 16.944  |
  | 3.4755        | 2.0   | 3750 | 3.7265          | 17.8066 | 4.4188 | 14.9432 | 15.5396   | 18.104  |
  | 3.2629        | 3.0   | 5625 | 3.7373          | 18.1202 | 4.6045 | 15.1273 | 15.7601   | 18.208  |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  