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: 3.6642
  - Rouge1: 12.9097
  - Rouge2: 3.2756
  - Rougel: 12.2885
  - Rougelsum: 12.3186
  
  ## 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: 16
  - eval_batch_size: 16
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | No log        | 1.0   | 300  | 5.0305          | 4.4679  | 0.4134 | 4.3487  | 4.2807    |
  | 9.3723        | 2.0   | 600  | 3.8535          | 10.6408 | 2.6198 | 10.5538 | 10.5819   |
  | 9.3723        | 3.0   | 900  | 3.7590          | 12.1502 | 3.3079 | 12.013  | 12.1208   |
  | 4.3429        | 4.0   | 1200 | 3.7019          | 13.0029 | 3.7708 | 12.9759 | 12.876    |
  | 4.3429        | 5.0   | 1500 | 3.6782          | 13.1362 | 3.0904 | 12.561  | 12.5702   |
  | 4.0043        | 6.0   | 1800 | 3.6698          | 12.8674 | 3.8026 | 12.3664 | 12.4216   |
  | 4.0043        | 7.0   | 2100 | 3.6644          | 12.9581 | 3.3843 | 12.407  | 12.3956   |
  | 3.872         | 8.0   | 2400 | 3.6642          | 12.9097 | 3.2756 | 12.2885 | 12.3186   |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  