readme: ---
  license: mit
  tags:
  - simplification
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mbart-large-50-clara-med
    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. -->
  
  # mbart-large-50-clara-med
  
  This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.2121
  - Rouge1: 49.1001
  - Rouge2: 31.2516
  - Rougel: 44.0446
  - Rougelsum: 44.1075
  
  ## 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: 5.6e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | No log        | 1.0   | 190  | 1.8633          | 44.8593 | 28.0451 | 40.7724 | 40.8654   |
  | No log        | 2.0   | 380  | 1.6667          | 46.8654 | 29.5857 | 42.6056 | 42.7844   |
  | 3.317         | 3.0   | 570  | 1.6847          | 48.1605 | 30.163  | 43.1965 | 43.3317   |
  | 3.317         | 4.0   | 760  | 1.7845          | 48.7615 | 30.8887 | 43.6946 | 43.8016   |
  | 0.7441        | 5.0   | 950  | 2.0090          | 48.4207 | 30.64   | 43.654  | 43.7979   |
  | 0.7441        | 6.0   | 1140 | 2.2425          | 49.1967 | 31.2644 | 44.0566 | 44.2112   |
  | 0.7441        | 7.0   | 1330 | 2.4520          | 47.0568 | 28.7501 | 41.8219 | 41.9605   |
  | 0.2396        | 8.0   | 1520 | 2.5336          | 47.969  | 30.0618 | 42.9924 | 43.1481   |
  | 0.2396        | 9.0   | 1710 | 2.6153          | 47.2037 | 28.9732 | 42.0939 | 42.2242   |
  | 0.1112        | 10.0  | 1900 | 2.7299          | 48.3657 | 30.3342 | 43.2025 | 43.3223   |
  | 0.1112        | 11.0  | 2090 | 2.7696          | 48.0929 | 30.0156 | 42.9385 | 43.026    |
  | 0.1112        | 12.0  | 2280 | 2.8627          | 48.1979 | 30.2714 | 43.0959 | 43.2027   |
  | 0.0938        | 13.0  | 2470 | 2.8788          | 47.7685 | 29.5733 | 42.7561 | 42.9112   |
  | 0.0938        | 14.0  | 2660 | 2.9128          | 47.5374 | 29.8217 | 42.7097 | 42.7803   |
  | 0.0394        | 15.0  | 2850 | 2.9470          | 48.6385 | 30.1425 | 43.3326 | 43.3963   |
  | 0.0394        | 16.0  | 3040 | 3.0039          | 48.6657 | 30.6642 | 43.471  | 43.592    |
  | 0.0394        | 17.0  | 3230 | 3.0380          | 48.2351 | 30.5653 | 43.257  | 43.3788   |
  | 0.023         | 18.0  | 3420 | 3.0289          | 48.6593 | 30.6916 | 43.7861 | 43.9098   |
  | 0.023         | 19.0  | 3610 | 3.0733          | 49.2114 | 31.2737 | 44.0852 | 44.1993   |
  | 0.0122        | 20.0  | 3800 | 3.1089          | 48.5431 | 30.5305 | 43.4128 | 43.5288   |
  | 0.0122        | 21.0  | 3990 | 3.0684          | 48.4197 | 30.4005 | 43.2305 | 43.3214   |
  | 0.0122        | 22.0  | 4180 | 3.1252          | 48.6007 | 30.5594 | 43.4008 | 43.5336   |
  | 0.0071        | 23.0  | 4370 | 3.1572          | 48.7297 | 30.7028 | 43.436  | 43.5106   |
  | 0.0071        | 24.0  | 4560 | 3.1716          | 48.9335 | 30.9918 | 43.7764 | 43.8044   |
  | 0.0041        | 25.0  | 4750 | 3.1687          | 48.8731 | 31.1055 | 43.8021 | 43.8987   |
  | 0.0041        | 26.0  | 4940 | 3.1845          | 48.9432 | 31.0766 | 43.8628 | 43.9726   |
  | 0.0041        | 27.0  | 5130 | 3.2133          | 49.2016 | 31.1265 | 44.052  | 44.1427   |
  | 0.0025        | 28.0  | 5320 | 3.2146          | 49.1473 | 31.3109 | 44.0372 | 44.1189   |
  | 0.0025        | 29.0  | 5510 | 3.2121          | 49.2815 | 31.4258 | 44.1661 | 44.2436   |
  | 0.0019        | 30.0  | 5700 | 3.2121          | 49.1001 | 31.2516 | 44.0446 | 44.1075   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0
  - Datasets 2.8.0
  - Tokenizers 0.12.1
  