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: 3.0346
  - Rouge1: 16.8527
  - Rouge2: 8.331
  - Rougel: 16.4475
  - Rougelsum: 16.6421
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 6.7536        | 1.0   | 1209 | 3.2881          | 13.6319 | 5.4635 | 13.0552 | 13.1093   |
  | 3.9312        | 2.0   | 2418 | 3.1490          | 16.8402 | 8.3559 | 16.1876 | 16.2869   |
  | 3.5987        | 3.0   | 3627 | 3.1043          | 17.9887 | 9.3136 | 17.3034 | 17.4313   |
  | 3.4261        | 4.0   | 4836 | 3.0573          | 17.0089 | 8.7389 | 16.5351 | 16.5023   |
  | 3.3221        | 5.0   | 6045 | 3.0569          | 16.8461 | 8.0988 | 16.4898 | 16.4927   |
  | 3.2549        | 6.0   | 7254 | 3.0511          | 17.3428 | 8.2234 | 16.7312 | 16.8749   |
  | 3.2067        | 7.0   | 8463 | 3.0334          | 16.268  | 7.9729 | 15.9342 | 16.0065   |
  | 3.1842        | 8.0   | 9672 | 3.0346          | 16.8527 | 8.331  | 16.4475 | 16.6421   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  