readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-paraphrase-finetuned-xsum-v3
    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-paraphrase-finetuned-xsum-v3
  
  This model is a fine-tuned version of [eugenesiow/bart-paraphrase](https://huggingface.co/eugenesiow/bart-paraphrase) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1881
  - Rouge1: 99.9251
  - Rouge2: 99.9188
  - Rougel: 99.9251
  - Rougelsum: 99.9251
  - Gen Len: 10.17
  
  ## 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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | No log        | 1.0   | 100  | 0.2702          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 10.38   |
  | No log        | 2.0   | 200  | 0.2773          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 11.45   |
  | No log        | 3.0   | 300  | 0.2178          | 99.8148 | 99.7051 | 99.8208 | 99.8148   | 11.19   |
  | No log        | 4.0   | 400  | 0.3649          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 12.32   |
  | 0.1561        | 5.0   | 500  | 0.2532          | 99.8957 | 99.8875 | 99.8957 | 99.8918   | 10.375  |
  | 0.1561        | 6.0   | 600  | 0.2050          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 11.15   |
  | 0.1561        | 7.0   | 700  | 0.2364          | 99.8957 | 99.8875 | 99.8957 | 99.8918   | 10.18   |
  | 0.1561        | 8.0   | 800  | 0.2006          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 10.17   |
  | 0.1561        | 9.0   | 900  | 0.1628          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 10.23   |
  | 0.1538        | 10.0  | 1000 | 0.1881          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 10.17   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  