readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-model2-3110-e4
    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-model2-3110-e4
  
  This model is a fine-tuned version of [theojolliffe/bart-paraphrase-v4-e1-feedback](https://huggingface.co/theojolliffe/bart-paraphrase-v4-e1-feedback) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0700
  - Rouge1: 70.0692
  - Rouge2: 68.1457
  - Rougel: 69.8943
  - Rougelsum: 70.0389
  - Gen Len: 19.8966
  
  ## 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: 6
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 0.5951        | 1.0   | 553  | 0.3089          | 62.5675 | 54.7411 | 61.2646 | 61.3675   | 19.7241 |
  | 0.2541        | 2.0   | 1106 | 0.1432          | 66.113  | 61.964  | 64.6141 | 64.9187   | 19.8966 |
  | 0.1547        | 3.0   | 1659 | 0.0964          | 68.6902 | 64.938  | 67.6197 | 67.9181   | 19.8966 |
  | 0.1141        | 4.0   | 2212 | 0.1015          | 68.9122 | 66.4279 | 68.4906 | 68.5758   | 19.8966 |
  | 0.0728        | 5.0   | 2765 | 0.0819          | 69.2271 | 66.8276 | 68.6915 | 68.849    | 19.8966 |
  | 0.0563        | 6.0   | 3318 | 0.0700          | 70.0692 | 68.1457 | 69.8943 | 70.0389   | 19.8966 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  