readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-paraphrase-finetuned-xsum-v4
    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-v4
  
  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: 1.1765
  - Rouge1: 49.972
  - Rouge2: 49.85
  - Rougel: 49.9165
  - Rougelsum: 49.7819
  - Gen Len: 8.3061
  
  ## 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   | 263  | 0.5050          | 47.9628 | 47.7085 | 47.8625 | 47.772    | 6.9639  |
  | 0.676         | 2.0   | 526  | 0.5793          | 49.6085 | 49.3495 | 49.5196 | 49.4173   | 7.4715  |
  | 0.676         | 3.0   | 789  | 0.7011          | 49.8635 | 49.6937 | 49.8155 | 49.6604   | 7.576   |
  | 0.322         | 4.0   | 1052 | 0.7585          | 49.8851 | 49.7578 | 49.8526 | 49.6977   | 7.6654  |
  | 0.322         | 5.0   | 1315 | 0.6615          | 49.861  | 49.7185 | 49.7978 | 49.6669   | 8.3023  |
  | 0.2828        | 6.0   | 1578 | 0.6233          | 49.916  | 49.7819 | 49.8861 | 49.7384   | 7.6084  |
  | 0.2828        | 7.0   | 1841 | 0.9380          | 49.916  | 49.7819 | 49.8861 | 49.7384   | 8.2433  |
  | 0.2073        | 8.0   | 2104 | 0.8497          | 49.9624 | 49.8355 | 49.91   | 49.7666   | 7.6331  |
  | 0.2073        | 9.0   | 2367 | 0.7715          | 49.972  | 49.85   | 49.9165 | 49.7819   | 7.9772  |
  | 0.1744        | 10.0  | 2630 | 1.1765          | 49.972  | 49.85   | 49.9165 | 49.7819   | 8.3061  |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  