readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-test-ged-RAW_data_prep_2021_12_26___t1_7.csv_max_target_length_10
    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. -->
  
  # mt5-small-test-ged-RAW_data_prep_2021_12_26___t1_7.csv_max_target_length_10
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0338
  - Rouge1: 28.7359
  - Rouge2: 15.6289
  - Rougel: 28.6407
  - Rougelsum: 28.7016
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 8
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | 6.0554        | 1.0   | 1935  | 2.7346          | 23.7306 | 13.3598 | 23.7172 | 23.7447   |
  | 2.9111        | 2.0   | 3870  | 2.3916          | 26.5211 | 14.5628 | 26.4827 | 26.5716   |
  | 2.464         | 3.0   | 5805  | 2.2382          | 27.4404 | 15.1211 | 27.3331 | 27.401    |
  | 2.2328        | 4.0   | 7740  | 2.1557          | 28.3377 | 14.7406 | 28.2386 | 28.249    |
  | 2.0845        | 5.0   | 9675  | 2.1324          | 29.1476 | 15.7579 | 29.0614 | 29.1701   |
  | 1.9825        | 6.0   | 11610 | 2.0668          | 28.4677 | 15.3332 | 28.4128 | 28.4093   |
  | 1.9233        | 7.0   | 13545 | 2.0441          | 28.6832 | 15.5251 | 28.5723 | 28.6479   |
  | 1.8842        | 8.0   | 15480 | 2.0338          | 28.7359 | 15.6289 | 28.6407 | 28.7016   |
  
  
  ### Framework versions
  
  - Transformers 4.20.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  