readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: paraphraser-spanish-t5-base
    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. -->
  
  # paraphraser-spanish-t5-base
  
  This model is a fine-tuned version of [milyiyo/paraphraser-spanish-t5-base](https://huggingface.co/milyiyo/paraphraser-spanish-t5-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7572
  
  ## 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: 2e-05
  - train_batch_size: 10
  - eval_batch_size: 10
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 1.1212        | 0.07  | 2000  | 0.8120          |
  | 1.2263        | 0.14  | 4000  | 0.7773          |
  | 1.1976        | 0.21  | 6000  | 0.7745          |
  | 1.1828        | 0.28  | 8000  | 0.7675          |
  | 1.1399        | 0.35  | 10000 | 0.7668          |
  | 1.1378        | 0.42  | 12000 | 0.7651          |
  | 1.1035        | 0.5   | 14000 | 0.7644          |
  | 1.0923        | 0.57  | 16000 | 0.7633          |
  | 1.0924        | 0.64  | 18000 | 0.7594          |
  | 1.0943        | 0.71  | 20000 | 0.7578          |
  | 1.0872        | 0.78  | 22000 | 0.7575          |
  | 1.0755        | 0.85  | 24000 | 0.7599          |
  | 1.0806        | 0.92  | 26000 | 0.7558          |
  | 1.079         | 0.99  | 28000 | 0.7572          |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  