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: 3.0294
  - Rouge1: 16.497
  - Rouge2: 8.0618
  - Rougel: 16.2979
  - Rougelsum: 16.1465
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 6.5928        | 1.0   | 1209 | 3.3005          | 14.7843 | 6.5518 | 14.2805 | 14.2951   |
  | 3.9024        | 2.0   | 2418 | 3.1399          | 16.8202 | 8.6739 | 16.1194 | 16.0844   |
  | 3.5806        | 3.0   | 3627 | 3.0869          | 18.1223 | 9.3051 | 17.7533 | 17.7254   |
  | 3.4201        | 4.0   | 4836 | 3.0590          | 17.654  | 9.0154 | 17.1853 | 17.1769   |
  | 3.3202        | 5.0   | 6045 | 3.0598          | 17.612  | 8.6707 | 17.4662 | 17.2963   |
  | 3.2436        | 6.0   | 7254 | 3.0409          | 16.7938 | 8.3054 | 16.6141 | 16.4853   |
  | 3.2079        | 7.0   | 8463 | 3.0332          | 16.7246 | 8.2362 | 16.5065 | 16.3611   |
  | 3.1801        | 8.0   | 9672 | 3.0294          | 16.497  | 8.0618 | 16.2979 | 16.1465   |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  