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 Xlsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.7436
  - Rouge1: 9.3908
  - Rouge2: 2.5077
  - RougeL: 7.8615
  - Rougelsum: 7.8745
  
  ## 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: 1
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 8
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 3.8301        | 1.0   | 3375  | 2.8828          | 8.1957 | 1.9439 | 6.8031 | 6.8206    |
  | 3.4032        | 2.0   | 6750  | 2.8049          | 8.9533 | 2.2919 | 7.4137 | 7.4244    |
  | 3.3697        | 3.0   | 10125 | 2.7743          | 9.3366 | 2.4531 | 7.8129 | 7.8276    |
  | 3.3862        | 4.0   | 13500 | 2.7500          | 9.4377 | 2.542  | 7.9123 | 7.9268    |
  | 3.1704        | 5.0   | 16875 | 2.7436          | 9.3908 | 2.5077 | 7.8615 | 7.8745    |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  