readme: ---
  license: apache-2.0
  tags:
  - multilingual model
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-multilingual-xlsum-new
    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-finetuned-multilingual-xlsum-new
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the 45 languages of the XL-Sum dataset.
  
  It achieves the following results on the evaluation set:
  - Loss: 2.7679
  - Rouge1: 9.1993
  - Rouge2: 2.3416
  - Rougel: 7.6684
  - Rougelsum: 7.7074
  
  ## 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: 2
  - eval_batch_size: 2
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 3.9684        | 1.0   | 1687 | 2.8902          | 8.0531 | 1.8357 | 6.7234 | 6.7401    |
  | 3.62          | 2.0   | 3374 | 2.8486          | 8.4881 | 2.0178 | 7.0542 | 7.0854    |
  | 3.3765        | 3.0   | 5061 | 2.7986          | 8.7796 | 2.2342 | 7.3363 | 7.3645    |
  | 3.5043        | 4.0   | 6748 | 2.7677          | 9.0486 | 2.3099 | 7.5493 | 7.5685    |
  | 3.338         | 5.0   | 8435 | 2.7679          | 9.1993 | 2.3416 | 7.6684 | 7.7074    |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  