---
tags:
- generated_from_trainer
datasets:
- ccmatrix
metrics:
- bleu
model-index:
- name: t5-base_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: 19.6396
---

<!-- 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_ro-finetuned-en-to-it

This model is a fine-tuned version of [j0hngou/t5-base-finetuned-en-to-ro](https://huggingface.co/j0hngou/t5-base-finetuned-en-to-ro) on the ccmatrix dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4669
- Bleu: 19.6396
- Gen Len: 52.4247

## 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   | 2.0942          | 5.6875  | 73.434  |
| 2.5108        | 2.0   | 564   | 1.9725          | 6.6631  | 72.6607 |
| 2.5108        | 3.0   | 846   | 1.9010          | 7.9227  | 67.01   |
| 2.1659        | 4.0   | 1128  | 1.8452          | 8.9935  | 65.1027 |
| 2.1659        | 5.0   | 1410  | 1.7979          | 9.4164  | 64.9827 |
| 2.0288        | 6.0   | 1692  | 1.7590          | 9.6035  | 66.6933 |
| 2.0288        | 7.0   | 1974  | 1.7264          | 10.7658 | 62.068  |
| 1.9238        | 8.0   | 2256  | 1.6955          | 11.5779 | 59.472  |
| 1.8435        | 9.0   | 2538  | 1.6729          | 12.7588 | 56.584  |
| 1.8435        | 10.0  | 2820  | 1.6541          | 13.3086 | 56.1153 |
| 1.775         | 11.0  | 3102  | 1.6337          | 13.8543 | 55.3307 |
| 1.775         | 12.0  | 3384  | 1.6148          | 14.3566 | 55.2853 |
| 1.7204        | 13.0  | 3666  | 1.5994          | 14.693  | 55.6607 |
| 1.7204        | 14.0  | 3948  | 1.5838          | 15.1284 | 55.5327 |
| 1.6705        | 15.0  | 4230  | 1.5742          | 15.6125 | 55.0087 |
| 1.632         | 16.0  | 4512  | 1.5600          | 15.9616 | 54.052  |
| 1.632         | 17.0  | 4794  | 1.5526          | 16.495  | 53.562  |
| 1.5868        | 18.0  | 5076  | 1.5392          | 16.4252 | 54.4613 |
| 1.5868        | 19.0  | 5358  | 1.5311          | 16.753  | 54.1853 |
| 1.5656        | 20.0  | 5640  | 1.5262          | 17.0308 | 54.2473 |
| 1.5656        | 21.0  | 5922  | 1.5186          | 17.3553 | 53.396  |
| 1.529         | 22.0  | 6204  | 1.5121          | 17.6177 | 53.472  |
| 1.529         | 23.0  | 6486  | 1.5058          | 17.6409 | 53.6847 |
| 1.5071        | 24.0  | 6768  | 1.5038          | 18.2009 | 53.2327 |
| 1.4903        | 25.0  | 7050  | 1.4962          | 18.4838 | 52.9587 |
| 1.4903        | 26.0  | 7332  | 1.4935          | 18.5545 | 52.688  |
| 1.4686        | 27.0  | 7614  | 1.4879          | 18.62   | 53.5    |
| 1.4686        | 28.0  | 7896  | 1.4850          | 19.0099 | 52.34   |
| 1.4511        | 29.0  | 8178  | 1.4813          | 19.0538 | 52.474  |
| 1.4511        | 30.0  | 8460  | 1.4787          | 18.89   | 53.0753 |
| 1.4364        | 31.0  | 8742  | 1.4756          | 19.2582 | 52.3587 |
| 1.4279        | 32.0  | 9024  | 1.4739          | 19.2973 | 52.69   |
| 1.4279        | 33.0  | 9306  | 1.4725          | 19.3624 | 52.694  |
| 1.4172        | 34.0  | 9588  | 1.4704          | 19.5421 | 52.1667 |
| 1.4172        | 35.0  | 9870  | 1.4689          | 19.4807 | 52.5487 |
| 1.4141        | 36.0  | 10152 | 1.4685          | 19.5972 | 52.2733 |
| 1.4141        | 37.0  | 10434 | 1.4676          | 19.5835 | 52.374  |
| 1.4058        | 38.0  | 10716 | 1.4674          | 19.6374 | 52.3447 |
| 1.4058        | 39.0  | 10998 | 1.4671          | 19.6105 | 52.5273 |
| 1.4027        | 40.0  | 11280 | 1.4669          | 19.6396 | 52.4247 |


### Framework versions

- Transformers 4.22.1
- Pytorch 1.12.1
- Datasets 2.5.1
- Tokenizers 0.11.0