readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-base-wikinewssum-italian
    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-base-wikinewssum-italian
  
  This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 10.5739
  - Rouge1: 2.1728
  - Rouge2: 0.1516
  - Rougel: 2.0846
  - Rougelsum: 2.0515
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 8
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | No log        | 1.0   | 8    | 16.6193         | 2.4011 | 0.3829 | 2.1505 | 2.2161    |
  | No log        | 2.0   | 16   | 15.8909         | 2.5165 | 0.2799 | 2.3403 | 2.3523    |
  | No log        | 3.0   | 24   | 15.4843         | 2.2794 | 0.2252 | 2.1849 | 2.1382    |
  | 17.2559       | 4.0   | 32   | 13.0850         | 2.2448 | 0.1516 | 2.1426 | 2.0859    |
  | 17.2559       | 5.0   | 40   | 11.7838         | 2.2448 | 0.1516 | 2.1426 | 2.0859    |
  | 17.2559       | 6.0   | 48   | 11.3207         | 2.2424 | 0.1516 | 2.1423 | 2.1171    |
  | 17.2559       | 7.0   | 56   | 10.7871         | 2.1081 | 0.1516 | 2.0227 | 1.9838    |
  | 14.6026       | 8.0   | 64   | 10.5739         | 2.1728 | 0.1516 | 2.0846 | 2.0515    |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.10.1
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  