readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - ccmatrix
  metrics:
  - bleu
  model-index:
  - name: t5-small-finetuned-en-to-it-b32
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: ccmatrix
        type: ccmatrix
        config: en-it
        split: train[3000:12000]
        args: en-it
      metrics:
      - name: Bleu
        type: bleu
        value: 9.6816
  ---
  
  <!-- 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-b32
  
  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: 2.1496
  - Bleu: 9.6816
  - Gen Len: 56.5347
  
  ## 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: 32
  - eval_batch_size: 32
  - 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   | 282   | 2.9409          | 2.6764 | 69.2487 |
  | 3.3809        | 2.0   | 564   | 2.8277          | 2.4974 | 87.428  |
  | 3.3809        | 3.0   | 846   | 2.7483          | 2.6851 | 89.7887 |
  | 3.1255        | 4.0   | 1128  | 2.6831          | 3.1801 | 85.6927 |
  | 3.1255        | 5.0   | 1410  | 2.6293          | 3.6949 | 79.9467 |
  | 2.9965        | 6.0   | 1692  | 2.5809          | 4.0149 | 76.852  |
  | 2.9965        | 7.0   | 1974  | 2.5403          | 4.3463 | 74.6487 |
  | 2.9002        | 8.0   | 2256  | 2.5033          | 4.838  | 72.6053 |
  | 2.8229        | 9.0   | 2538  | 2.4694          | 5.2829 | 67.984  |
  | 2.8229        | 10.0  | 2820  | 2.4421          | 5.4964 | 68.986  |
  | 2.76          | 11.0  | 3102  | 2.4135          | 5.8118 | 66.528  |
  | 2.76          | 12.0  | 3384  | 2.3897          | 6.1966 | 65.052  |
  | 2.7051        | 13.0  | 3666  | 2.3667          | 6.452  | 64.2273 |
  | 2.7051        | 14.0  | 3948  | 2.3465          | 6.6428 | 63.516  |
  | 2.6568        | 15.0  | 4230  | 2.3265          | 6.9467 | 61.8673 |
  | 2.6183        | 16.0  | 4512  | 2.3101          | 7.2029 | 60.7393 |
  | 2.6183        | 17.0  | 4794  | 2.2954          | 7.4982 | 60.0327 |
  | 2.5757        | 18.0  | 5076  | 2.2799          | 7.7555 | 59.968  |
  | 2.5757        | 19.0  | 5358  | 2.2660          | 7.8406 | 60.0307 |
  | 2.5534        | 20.0  | 5640  | 2.2558          | 8.0679 | 59.0793 |
  | 2.5534        | 21.0  | 5922  | 2.2426          | 8.3325 | 58.5367 |
  | 2.5159        | 22.0  | 6204  | 2.2324          | 8.3538 | 58.6893 |
  | 2.5159        | 23.0  | 6486  | 2.2217          | 8.5867 | 57.7627 |
  | 2.4983        | 24.0  | 6768  | 2.2135          | 8.8324 | 56.7367 |
  | 2.4791        | 25.0  | 7050  | 2.2052          | 8.8113 | 57.4373 |
  | 2.4791        | 26.0  | 7332  | 2.1981          | 9.0909 | 57.0173 |
  | 2.4529        | 27.0  | 7614  | 2.1908          | 9.0056 | 57.802  |
  | 2.4529        | 28.0  | 7896  | 2.1856          | 9.2696 | 56.9773 |
  | 2.4395        | 29.0  | 8178  | 2.1780          | 9.2824 | 57.0007 |
  | 2.4395        | 30.0  | 8460  | 2.1722          | 9.2106 | 56.9893 |
  | 2.4277        | 31.0  | 8742  | 2.1685          | 9.4668 | 56.406  |
  | 2.4181        | 32.0  | 9024  | 2.1646          | 9.4992 | 56.2327 |
  | 2.4181        | 33.0  | 9306  | 2.1616          | 9.5054 | 56.3033 |
  | 2.4071        | 34.0  | 9588  | 2.1578          | 9.5093 | 56.548  |
  | 2.4071        | 35.0  | 9870  | 2.1554          | 9.5227 | 56.7807 |
  | 2.3991        | 36.0  | 10152 | 2.1532          | 9.5762 | 56.756  |
  | 2.3991        | 37.0  | 10434 | 2.1518          | 9.6659 | 56.5913 |
  | 2.3955        | 38.0  | 10716 | 2.1506          | 9.7199 | 56.5753 |
  | 2.3955        | 39.0  | 10998 | 2.1498          | 9.6715 | 56.558  |
  | 2.3913        | 40.0  | 11280 | 2.1496          | 9.6816 | 56.5347 |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1
  - Datasets 2.5.1
  - Tokenizers 0.11.0
  