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: 0.3377
  - Rouge1: 99.9461
  - Rouge2: 72.6619
  - Rougel: 99.9461
  - Rougelsum: 99.9461
  - Gen Len: 9.0396
  
  ## 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   | 139  | 0.3653          | 96.4972 | 70.8271 | 96.5252 | 96.5085   | 9.7158  |
  | No log        | 2.0   | 278  | 0.6624          | 98.3228 | 72.2829 | 98.2598 | 98.2519   | 9.0612  |
  | No log        | 3.0   | 417  | 0.2880          | 98.2415 | 72.36   | 98.249  | 98.2271   | 9.4496  |
  | 0.5019        | 4.0   | 556  | 0.4188          | 98.1123 | 70.8536 | 98.0746 | 98.0465   | 9.4065  |
  | 0.5019        | 5.0   | 695  | 0.3718          | 98.8882 | 72.6619 | 98.8997 | 98.8882   | 10.7842 |
  | 0.5019        | 6.0   | 834  | 0.4442          | 99.6076 | 72.6619 | 99.6076 | 99.598    | 9.0647  |
  | 0.5019        | 7.0   | 973  | 0.2681          | 99.6076 | 72.6619 | 99.598  | 99.598    | 9.1403  |
  | 0.2751        | 8.0   | 1112 | 0.3577          | 99.2479 | 72.6619 | 99.2536 | 99.2383   | 9.0612  |
  | 0.2751        | 9.0   | 1251 | 0.2481          | 98.8785 | 72.6394 | 98.8882 | 98.8882   | 9.7914  |
  | 0.2751        | 10.0  | 1390 | 0.2339          | 99.6076 | 72.6619 | 99.6076 | 99.6076   | 9.1942  |
  | 0.2051        | 11.0  | 1529 | 0.2472          | 99.9461 | 72.6619 | 99.9461 | 99.9461   | 9.2338  |
  | 0.2051        | 12.0  | 1668 | 0.3948          | 99.6076 | 72.6619 | 99.598  | 99.598    | 9.0468  |
  | 0.2051        | 13.0  | 1807 | 0.4756          | 99.6076 | 72.6619 | 99.6076 | 99.6076   | 9.0576  |
  | 0.2051        | 14.0  | 1946 | 0.3543          | 99.9461 | 72.6619 | 99.9461 | 99.9461   | 9.0396  |
  | 0.1544        | 15.0  | 2085 | 0.2828          | 99.9461 | 72.6619 | 99.9461 | 99.9461   | 9.0576  |
  | 0.1544        | 16.0  | 2224 | 0.2456          | 99.9461 | 72.6619 | 99.9461 | 99.9461   | 9.1079  |
  | 0.1544        | 17.0  | 2363 | 0.2227          | 99.9461 | 72.6394 | 99.9461 | 99.9461   | 9.5072  |
  | 0.1285        | 18.0  | 2502 | 0.3490          | 99.9461 | 72.6619 | 99.9461 | 99.9461   | 9.0396  |
  | 0.1285        | 19.0  | 2641 | 0.3736          | 99.9461 | 72.6619 | 99.9461 | 99.9461   | 9.0396  |
  | 0.1285        | 20.0  | 2780 | 0.3377          | 99.9461 | 72.6619 | 99.9461 | 99.9461   | 9.0396  |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  