readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - ccmatrix
  metrics:
  - bleu
  model-index:
  - name: t5-base-finetuned-it-to-en
    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: 26.0557
  ---
  
  <!-- 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-base-finetuned-it-to-en
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the ccmatrix dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7418
  - Bleu: 26.0557
  - Gen Len: 25.6033
  
  ## 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   | 2.0555          | 16.8117 | 26.9573 |
  | 2.3228        | 2.0   | 564   | 1.9791          | 18.207  | 26.754  |
  | 2.3228        | 3.0   | 846   | 1.9340          | 19.2206 | 26.6513 |
  | 2.104         | 4.0   | 1128  | 1.8999          | 20.0802 | 26.5473 |
  | 2.104         | 5.0   | 1410  | 1.8741          | 20.9222 | 26.4633 |
  | 1.9952        | 6.0   | 1692  | 1.8511          | 21.3    | 26.4547 |
  | 1.9952        | 7.0   | 1974  | 1.8361          | 21.9444 | 26.5227 |
  | 1.9032        | 8.0   | 2256  | 1.8191          | 22.224  | 26.168  |
  | 1.8342        | 9.0   | 2538  | 1.8074          | 22.7097 | 26.1573 |
  | 1.8342        | 10.0  | 2820  | 1.7972          | 23.0299 | 26.2373 |
  | 1.7718        | 11.0  | 3102  | 1.7898          | 23.5173 | 26.0447 |
  | 1.7718        | 12.0  | 3384  | 1.7833          | 23.7157 | 26.0073 |
  | 1.7268        | 13.0  | 3666  | 1.7785          | 23.8523 | 25.742  |
  | 1.7268        | 14.0  | 3948  | 1.7725          | 23.979  | 25.88   |
  | 1.6822        | 15.0  | 4230  | 1.7686          | 24.2126 | 25.8347 |
  | 1.6386        | 16.0  | 4512  | 1.7639          | 24.4612 | 25.786  |
  | 1.6386        | 17.0  | 4794  | 1.7605          | 24.6716 | 25.828  |
  | 1.6047        | 18.0  | 5076  | 1.7549          | 24.9392 | 25.6493 |
  | 1.6047        | 19.0  | 5358  | 1.7548          | 24.8965 | 25.6527 |
  | 1.5778        | 20.0  | 5640  | 1.7537          | 24.9908 | 25.7827 |
  | 1.5778        | 21.0  | 5922  | 1.7498          | 25.1397 | 25.6707 |
  | 1.5413        | 22.0  | 6204  | 1.7472          | 25.2764 | 25.7373 |
  | 1.5413        | 23.0  | 6486  | 1.7468          | 25.3103 | 25.6927 |
  | 1.5249        | 24.0  | 6768  | 1.7471          | 25.3128 | 25.698  |
  | 1.5052        | 25.0  | 7050  | 1.7449          | 25.4046 | 25.6813 |
  | 1.5052        | 26.0  | 7332  | 1.7444          | 25.5513 | 25.7833 |
  | 1.4825        | 27.0  | 7614  | 1.7448          | 25.4756 | 25.632  |
  | 1.4825        | 28.0  | 7896  | 1.7432          | 25.6046 | 25.658  |
  | 1.4665        | 29.0  | 8178  | 1.7422          | 25.6138 | 25.6907 |
  | 1.4665        | 30.0  | 8460  | 1.7420          | 25.7196 | 25.7    |
  | 1.4508        | 31.0  | 8742  | 1.7420          | 25.8684 | 25.618  |
  | 1.4394        | 32.0  | 9024  | 1.7420          | 25.8188 | 25.6007 |
  | 1.4394        | 33.0  | 9306  | 1.7417          | 25.9295 | 25.6113 |
  | 1.4318        | 34.0  | 9588  | 1.7421          | 25.9842 | 25.614  |
  | 1.4318        | 35.0  | 9870  | 1.7408          | 26.1045 | 25.5933 |
  | 1.4244        | 36.0  | 10152 | 1.7409          | 26.0496 | 25.6327 |
  | 1.4244        | 37.0  | 10434 | 1.7417          | 26.0595 | 25.6347 |
  | 1.4139        | 38.0  | 10716 | 1.7420          | 26.0515 | 25.6047 |
  | 1.4139        | 39.0  | 10998 | 1.7417          | 26.0727 | 25.616  |
  | 1.4135        | 40.0  | 11280 | 1.7418          | 26.0557 | 25.6033 |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1
  - Datasets 2.5.1
  - Tokenizers 0.11.0
  