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 None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.7673
  - Rouge1: 9.1368
  - Rouge2: 2.3893
  - Rougel: 7.6599
  - Rougelsum: 7.6873
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 3.7827        | 1.0   | 1687 | 2.8911          | 8.1314 | 1.9569 | 6.7927 | 6.8179    |
  | 3.6518        | 2.0   | 3374 | 2.8338          | 8.6621 | 2.1437 | 7.2171 | 7.246     |
  | 3.3691        | 3.0   | 5061 | 2.8015          | 8.9402 | 2.2733 | 7.4744 | 7.497     |
  | 3.4435        | 4.0   | 6748 | 2.7746          | 9.0514 | 2.3627 | 7.6144 | 7.6358    |
  | 3.5139        | 5.0   | 8435 | 2.7673          | 9.1368 | 2.3893 | 7.6599 | 7.6873    |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  