readme: ---
  tags:
  - simplification
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-xsum-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. -->
  
  # pegasus-xsum-clara-med
  
  This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8180
  - Rouge1: 43.7763
  - Rouge2: 26.3466
  - Rougel: 39.8012
  - Rougelsum: 39.9372
  
  ## 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  | 2.4930          | 41.6573 | 24.6944 | 38.1397 | 38.2281   |
  | No log        | 2.0   | 380  | 2.3040          | 41.8566 | 24.8221 | 38.3536 | 38.4388   |
  | 2.7991        | 3.0   | 570  | 2.1948          | 42.3763 | 25.2507 | 38.8428 | 38.9332   |
  | 2.7991        | 4.0   | 760  | 2.1125          | 42.594  | 25.3387 | 38.9852 | 39.0943   |
  | 2.2847        | 5.0   | 950  | 2.0572          | 42.787  | 25.4389 | 39.0955 | 39.2058   |
  | 2.2847        | 6.0   | 1140 | 2.0060          | 42.5352 | 25.4116 | 38.9543 | 39.0612   |
  | 2.2847        | 7.0   | 1330 | 1.9763          | 43.1491 | 25.8284 | 39.4736 | 39.5408   |
  | 2.045         | 8.0   | 1520 | 1.9450          | 42.9045 | 25.6443 | 39.199  | 39.3001   |
  | 2.045         | 9.0   | 1710 | 1.9211          | 43.4467 | 26.1193 | 39.6719 | 39.7851   |
  | 1.8913        | 10.0  | 1900 | 1.9068          | 43.4686 | 26.3111 | 39.8135 | 39.9415   |
  | 1.8913        | 11.0  | 2090 | 1.8846          | 43.6095 | 26.5185 | 39.939  | 40.0718   |
  | 1.8913        | 12.0  | 2280 | 1.8715          | 43.6946 | 26.6905 | 39.8639 | 40.0241   |
  | 1.7674        | 13.0  | 2470 | 1.8565          | 43.5853 | 26.7413 | 39.8926 | 40.0166   |
  | 1.7674        | 14.0  | 2660 | 1.8612          | 43.7848 | 26.7362 | 39.9825 | 40.1077   |
  | 1.6771        | 15.0  | 2850 | 1.8428          | 43.8553 | 26.8044 | 40.1223 | 40.2544   |
  | 1.6771        | 16.0  | 3040 | 1.8325          | 43.6724 | 26.7693 | 39.8928 | 40.0302   |
  | 1.6771        | 17.0  | 3230 | 1.8314          | 44.0667 | 26.9233 | 40.2983 | 40.453    |
  | 1.596         | 18.0  | 3420 | 1.8262          | 44.1355 | 26.9904 | 40.303  | 40.4696   |
  | 1.596         | 19.0  | 3610 | 1.8296          | 44.0241 | 26.8979 | 40.1958 | 40.3237   |
  | 1.5382        | 20.0  | 3800 | 1.8269          | 43.865  | 26.6328 | 39.996  | 40.1305   |
  | 1.5382        | 21.0  | 3990 | 1.8191          | 44.2095 | 27.0096 | 40.408  | 40.5267   |
  | 1.5382        | 22.0  | 4180 | 1.8189          | 44.0012 | 26.9301 | 40.1486 | 40.2899   |
  | 1.4907        | 23.0  | 4370 | 1.8197          | 43.8548 | 26.451  | 39.9191 | 40.0946   |
  | 1.4907        | 24.0  | 4560 | 1.8235          | 43.9574 | 26.527  | 39.9989 | 40.1509   |
  | 1.4504        | 25.0  | 4750 | 1.8164          | 43.984  | 26.5925 | 40.0355 | 40.1654   |
  | 1.4504        | 26.0  | 4940 | 1.8166          | 43.9485 | 26.4552 | 40.0596 | 40.1776   |
  | 1.4504        | 27.0  | 5130 | 1.8174          | 43.814  | 26.2743 | 39.8467 | 39.9708   |
  | 1.4225        | 28.0  | 5320 | 1.8185          | 43.8619 | 26.293  | 39.8523 | 40.0167   |
  | 1.4225        | 29.0  | 5510 | 1.8190          | 43.7938 | 26.3853 | 39.8207 | 39.9445   |
  | 1.4188        | 30.0  | 5700 | 1.8180          | 43.7763 | 26.3466 | 39.8012 | 39.9372   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0
  - Datasets 2.8.0
  - Tokenizers 0.12.1
  