readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-paraphrase-finetuned-xsum-v2
    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-v2
  
  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: 0.2329
  - Rouge1: 100.0
  - Rouge2: 100.0
  - Rougel: 100.0
  - Rougelsum: 100.0
  - Gen Len: 9.2619
  
  ## 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: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | No log        | 1.0   | 21   | 1.2954          | 66.7012 | 60.8612 | 66.5163 | 66.4352   | 13.2857 |
  | No log        | 2.0   | 42   | 0.6866          | 86.8284 | 82.7835 | 86.7208 | 86.784    | 9.5238  |
  | No log        | 3.0   | 63   | 0.4652          | 95.1892 | 93.5619 | 95.2567 | 95.1657   | 10.3095 |
  | No log        | 4.0   | 84   | 0.4280          | 97.7463 | 97.1782 | 97.8708 | 97.718    | 9.5     |
  | No log        | 5.0   | 105  | 0.3712          | 99.6435 | 99.5767 | 99.6435 | 99.6435   | 9.3571  |
  | No log        | 6.0   | 126  | 0.4451          | 99.2695 | 98.9418 | 99.1883 | 99.3506   | 9.3095  |
  | No log        | 7.0   | 147  | 0.3169          | 99.246  | 99.0232 | 99.246  | 99.4048   | 9.619   |
  | No log        | 8.0   | 168  | 0.2942          | 100.0   | 100.0   | 100.0   | 100.0     | 9.4048  |
  | No log        | 9.0   | 189  | 0.3105          | 100.0   | 100.0   | 100.0   | 100.0     | 9.1667  |
  | No log        | 10.0  | 210  | 0.3035          | 100.0   | 100.0   | 100.0   | 100.0     | 9.2619  |
  | No log        | 11.0  | 231  | 0.2983          | 100.0   | 100.0   | 100.0   | 100.0     | 10.5714 |
  | No log        | 12.0  | 252  | 0.2497          | 100.0   | 100.0   | 100.0   | 100.0     | 9.4286  |
  | No log        | 13.0  | 273  | 0.2911          | 100.0   | 100.0   | 100.0   | 100.0     | 9.1667  |
  | No log        | 14.0  | 294  | 0.2619          | 100.0   | 100.0   | 100.0   | 100.0     | 9.2143  |
  | No log        | 15.0  | 315  | 0.2510          | 100.0   | 100.0   | 100.0   | 100.0     | 9.2381  |
  | No log        | 16.0  | 336  | 0.2647          | 100.0   | 100.0   | 100.0   | 100.0     | 9.9048  |
  | No log        | 17.0  | 357  | 0.2438          | 100.0   | 100.0   | 100.0   | 100.0     | 9.2143  |
  | No log        | 18.0  | 378  | 0.2324          | 100.0   | 100.0   | 100.0   | 100.0     | 9.3095  |
  | No log        | 19.0  | 399  | 0.2296          | 100.0   | 100.0   | 100.0   | 100.0     | 9.3095  |
  | No log        | 20.0  | 420  | 0.2329          | 100.0   | 100.0   | 100.0   | 100.0     | 9.2619  |
  
  
  ### Framework versions
  
  - Transformers 4.19.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  