readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - ccmatrix
  metrics:
  - bleu
  model-index:
  - name: t5-small_ro-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[3000:12000]
        args: en-it
      metrics:
      - name: Bleu
        type: bleu
        value: 7.11
  ---
  
  <!-- 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_ro-finetuned-en-to-it
  
  This model is a fine-tuned version of [din0s/t5-small-finetuned-en-to-ro](https://huggingface.co/din0s/t5-small-finetuned-en-to-ro) on the ccmatrix dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3301
  - Bleu: 7.11
  - Gen Len: 59.538
  
  ## 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   | 94   | 3.1873          | 1.8829 | 94.336  |
  | No log        | 2.0   | 188  | 3.0132          | 2.5572 | 83.6413 |
  | No log        | 3.0   | 282  | 2.9226          | 3.0999 | 76.166  |
  | No log        | 4.0   | 376  | 2.8559          | 3.3859 | 73.906  |
  | No log        | 5.0   | 470  | 2.8040          | 3.8793 | 70.5667 |
  | 3.4136        | 6.0   | 564  | 2.7585          | 3.8974 | 69.404  |
  | 3.4136        | 7.0   | 658  | 2.7191          | 4.1236 | 68.6387 |
  | 3.4136        | 8.0   | 752  | 2.6836          | 4.3281 | 67.682  |
  | 3.4136        | 9.0   | 846  | 2.6509          | 4.343  | 67.0113 |
  | 3.4136        | 10.0  | 940  | 2.6231          | 4.561  | 66.094  |
  | 3.0128        | 11.0  | 1034 | 2.5984          | 4.9314 | 64.3033 |
  | 3.0128        | 12.0  | 1128 | 2.5755          | 5.0149 | 64.502  |
  | 3.0128        | 13.0  | 1222 | 2.5529          | 5.0758 | 65.194  |
  | 3.0128        | 14.0  | 1316 | 2.5332          | 5.2774 | 64.0773 |
  | 3.0128        | 15.0  | 1410 | 2.5128          | 5.3165 | 64.5213 |
  | 2.859         | 16.0  | 1504 | 2.4976          | 5.4714 | 62.884  |
  | 2.859         | 17.0  | 1598 | 2.4803          | 5.532  | 63.9593 |
  | 2.859         | 18.0  | 1692 | 2.4662          | 5.6314 | 63.7273 |
  | 2.859         | 19.0  | 1786 | 2.4529          | 5.8855 | 62.8953 |
  | 2.859         | 20.0  | 1880 | 2.4401          | 6.1225 | 61.496  |
  | 2.859         | 21.0  | 1974 | 2.4285          | 6.2697 | 60.034  |
  | 2.7544        | 22.0  | 2068 | 2.4171          | 6.4153 | 60.6027 |
  | 2.7544        | 23.0  | 2162 | 2.4067          | 6.3731 | 61.08   |
  | 2.7544        | 24.0  | 2256 | 2.3974          | 6.5355 | 61.3707 |
  | 2.7544        | 25.0  | 2350 | 2.3882          | 6.5259 | 60.966  |
  | 2.7544        | 26.0  | 2444 | 2.3808          | 6.7178 | 60.1707 |
  | 2.6867        | 27.0  | 2538 | 2.3733          | 6.8196 | 60.398  |
  | 2.6867        | 28.0  | 2632 | 2.3672          | 6.811  | 60.2753 |
  | 2.6867        | 29.0  | 2726 | 2.3609          | 6.8322 | 60.0973 |
  | 2.6867        | 30.0  | 2820 | 2.3551          | 6.8524 | 60.16   |
  | 2.6867        | 31.0  | 2914 | 2.3502          | 6.8363 | 60.2867 |
  | 2.6395        | 32.0  | 3008 | 2.3455          | 6.9495 | 59.8547 |
  | 2.6395        | 33.0  | 3102 | 2.3422          | 6.9939 | 59.4813 |
  | 2.6395        | 34.0  | 3196 | 2.3387          | 6.9953 | 59.812  |
  | 2.6395        | 35.0  | 3290 | 2.3362          | 7.0318 | 59.8813 |
  | 2.6395        | 36.0  | 3384 | 2.3339          | 7.1114 | 59.232  |
  | 2.6395        | 37.0  | 3478 | 2.3322          | 7.1488 | 59.292  |
  | 2.6138        | 38.0  | 3572 | 2.3310          | 7.1334 | 59.6093 |
  | 2.6138        | 39.0  | 3666 | 2.3303          | 7.0984 | 59.6887 |
  | 2.6138        | 40.0  | 3760 | 2.3301          | 7.11   | 59.538  |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1
  - Datasets 2.5.1
  - Tokenizers 0.11.0
  