readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: BARTkrame-abstract
    results: []
  widget:
  - text: "Nous voulons que tous les êtres humains, ensemble ou pris isolément, jeunes ou vieux, riches ou pauvres, nobles ou roturiers, hommes ou femmes, puissent pleinement s'instruire et devenir des êtres achevés. Nous voulons qu'ils soient instruits parfaitement et formés non seulement sur tel ou tel point, mais également sur tout ce qui permet à l'homme de réaliser intégralement son essence"
  ---
  
  <!-- 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. -->
  
  # BARTkrame-abstract
  
  This model is a fine-tuned version of [krm/BARTkrame-abstract](https://huggingface.co/krm/BARTkrame-abstract) on the [krm/for-ULPGL-Dissertation](https://huggingface.co/datasets/krm/for-ULPGL-Dissertation) dataset.
  It achieves (15/10/2022) the following results on the evaluation set:
  - Loss: 2.4196
  - Rouge1: 0.2703
  - Rouge2: 0.1334
  - Rougel: 0.2392
  - Rougelsum: 0.2419
  
  ## Model description
  
  This model is primarly a finetuned version of [moussaKam/mbarthez](https://huggingface.co/moussaKam/mbarthez).
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  We have used the [krm/for-ULPGL-Dissertation](https://huggingface.co/datasets/krm/for-ULPGL-Dissertation) dataset reduced to :
  
  > **Training data :** **5000** samples taken at random with *seed=42*.
  
  > **Validation data :** **100** samples taken at random with *seed=42*.
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5.6e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9, 0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 12
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 0.1316        | 9.0   | 1250 | 2.3251          | 0.2505 | 0.1158 | 0.2150 | 0.2184    |
  | 0.0894        | 10.0   | 2500 | 2.3467          | 0.2526 | 0.1073 | 0.2067 | 0.2124    |
  | 0.045         | 11.0   | 3750 | 2.3742          | 0.2593 | 0.1211 | 0.2281 | 0.2308    |
  | 0.0242        | 12.0   | 5000 | 2.4196          | 0.2703 | 0.1334 | 0.2392 | 0.2419    |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  