readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-amazon-en-es
    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-amazon-en-es
  
  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: 3.2891
  - Rouge1: 15.35
  - Rouge2: 6.4925
  - Rougel: 14.8921
  - Rougelsum: 14.6312
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 7.0622        | 1.0   | 1276  | 3.5617          | 13.2417 | 4.8928 | 12.8258 | 12.8078   |
  | 4.0768        | 2.0   | 2552  | 3.4329          | 14.5681 | 6.4922 | 14.0621 | 13.9709   |
  | 3.7736        | 3.0   | 3828  | 3.3393          | 15.1942 | 6.5262 | 14.7138 | 14.6049   |
  | 3.5951        | 4.0   | 5104  | 3.3122          | 14.8813 | 6.2962 | 14.507  | 14.3477   |
  | 3.477         | 5.0   | 6380  | 3.2991          | 15.0992 | 6.3888 | 14.8397 | 14.5606   |
  | 3.4084        | 6.0   | 7656  | 3.3035          | 15.1897 | 6.2292 | 14.6686 | 14.4488   |
  | 3.3661        | 7.0   | 8932  | 3.2959          | 15.3489 | 6.5702 | 14.9211 | 14.701    |
  | 3.3457        | 8.0   | 10208 | 3.2891          | 15.35   | 6.4925 | 14.8921 | 14.6312   |
  
  
  ### Framework versions
  
  - Transformers 4.19.1
  - Pytorch 1.7.0
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  