readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-base-wikinewssum-polish
    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-polish
  
  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: 2.3179
  - Rouge1: 7.911
  - Rouge2: 3.2189
  - Rougel: 6.7856
  - Rougelsum: 7.4485
  
  ## 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   | 315  | 2.5391          | 5.9874 | 2.3594 | 5.1303 | 5.6116    |
  | No log        | 2.0   | 630  | 2.4446          | 7.7294 | 3.0152 | 6.6024 | 7.2757    |
  | No log        | 3.0   | 945  | 2.3912          | 7.6451 | 2.9785 | 6.5714 | 7.2011    |
  | 3.5311        | 4.0   | 1260 | 2.3720          | 7.8007 | 3.0913 | 6.7067 | 7.3451    |
  | 3.5311        | 5.0   | 1575 | 2.3411          | 7.8374 | 3.1208 | 6.7288 | 7.3459    |
  | 3.5311        | 6.0   | 1890 | 2.3354          | 7.8664 | 3.1655 | 6.762  | 7.4364    |
  | 3.5311        | 7.0   | 2205 | 2.3175          | 7.9529 | 3.2225 | 6.8438 | 7.4904    |
  | 2.692         | 8.0   | 2520 | 2.3179          | 7.911  | 3.2189 | 6.7856 | 7.4485    |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.10.1
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  