readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - ccmatrix
  metrics:
  - bleu
  model-index:
  - name: t5-small-finetuned-en-to-it
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: ccmatrix
        type: ccmatrix
        config: en-it
        split: train[3000:15000]
        args: en-it
      metrics:
      - name: Bleu
        type: bleu
        value: 7.3298
  ---
  
  <!-- 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. -->
  
  # t5-small-finetuned-en-to-it
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the ccmatrix dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.2698
  - Bleu: 7.3298
  - Gen Len: 62.3753
  
  ## 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: 96
  - eval_batch_size: 96
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 40
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
  | No log        | 1.0   | 125  | 3.0010          | 2.7294 | 56.4513 |
  | No log        | 2.0   | 250  | 2.8999          | 2.3228 | 81.4993 |
  | No log        | 3.0   | 375  | 2.8281          | 2.3065 | 92.3353 |
  | 3.3202        | 4.0   | 500  | 2.7722          | 2.5982 | 91.8093 |
  | 3.3202        | 5.0   | 625  | 2.7254          | 2.9279 | 89.0907 |
  | 3.3202        | 6.0   | 750  | 2.6839          | 3.0747 | 89.2827 |
  | 3.3202        | 7.0   | 875  | 2.6470          | 3.207  | 87.948  |
  | 3.0355        | 8.0   | 1000 | 2.6132          | 3.355  | 85.2487 |
  | 3.0355        | 9.0   | 1125 | 2.5835          | 3.8401 | 80.578  |
  | 3.0355        | 10.0  | 1250 | 2.5552          | 4.2905 | 75.818  |
  | 3.0355        | 11.0  | 1375 | 2.5323          | 4.3866 | 75.2433 |
  | 2.8903        | 12.0  | 1500 | 2.5079          | 4.5687 | 74.906  |
  | 2.8903        | 13.0  | 1625 | 2.4881          | 4.7844 | 71.5773 |
  | 2.8903        | 14.0  | 1750 | 2.4668          | 4.876  | 71.68   |
  | 2.8903        | 15.0  | 1875 | 2.4485          | 5.1292 | 70.118  |
  | 2.7891        | 16.0  | 2000 | 2.4322          | 5.3297 | 68.894  |
  | 2.7891        | 17.0  | 2125 | 2.4161          | 5.555  | 68.2293 |
  | 2.7891        | 18.0  | 2250 | 2.4010          | 5.7113 | 67.2907 |
  | 2.7891        | 19.0  | 2375 | 2.3892          | 5.9105 | 66.6287 |
  | 2.713         | 20.0  | 2500 | 2.3756          | 6.0057 | 66.112  |
  | 2.713         | 21.0  | 2625 | 2.3643          | 6.3118 | 64.6193 |
  | 2.713         | 22.0  | 2750 | 2.3533          | 6.476  | 64.31   |
  | 2.713         | 23.0  | 2875 | 2.3432          | 6.7102 | 63.5467 |
  | 2.6584        | 24.0  | 3000 | 2.3342          | 6.7604 | 63.6567 |
  | 2.6584        | 25.0  | 3125 | 2.3253          | 6.8418 | 63.6573 |
  | 2.6584        | 26.0  | 3250 | 2.3180          | 6.9165 | 63.5893 |
  | 2.6584        | 27.0  | 3375 | 2.3120          | 7.0217 | 63.1033 |
  | 2.616         | 28.0  | 3500 | 2.3056          | 6.9148 | 63.598  |
  | 2.616         | 29.0  | 3625 | 2.2987          | 6.9961 | 63.6267 |
  | 2.616         | 30.0  | 3750 | 2.2935          | 7.2238 | 62.8373 |
  | 2.616         | 31.0  | 3875 | 2.2892          | 7.1906 | 62.7793 |
  | 2.587         | 32.0  | 4000 | 2.2849          | 7.2052 | 63.126  |
  | 2.587         | 33.0  | 4125 | 2.2815          | 7.3272 | 62.526  |
  | 2.587         | 34.0  | 4250 | 2.2782          | 7.3603 | 62.4313 |
  | 2.587         | 35.0  | 4375 | 2.2756          | 7.3072 | 62.6307 |
  | 2.5673        | 36.0  | 4500 | 2.2737          | 7.3586 | 62.1633 |
  | 2.5673        | 37.0  | 4625 | 2.2718          | 7.3485 | 62.358  |
  | 2.5673        | 38.0  | 4750 | 2.2707          | 7.3406 | 62.298  |
  | 2.5673        | 39.0  | 4875 | 2.2700          | 7.3233 | 62.42   |
  | 2.5591        | 40.0  | 5000 | 2.2698          | 7.3298 | 62.3753 |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1
  - Datasets 2.5.1
  - Tokenizers 0.11.0
  