---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- ccmatrix
metrics:
- bleu
model-index:
- name: t5-base-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: 20.1194
---

<!-- 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-en-to-it

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: 1.4830
- Bleu: 20.1194
- Gen Len: 51.456

## 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   | 2.0137          | 6.5621  | 69.0227 |
| 2.4006        | 2.0   | 564   | 1.9278          | 7.2684  | 70.0333 |
| 2.4006        | 3.0   | 846   | 1.8712          | 8.6643  | 64.654  |
| 2.1423        | 4.0   | 1128  | 1.8223          | 9.3778  | 63.4453 |
| 2.1423        | 5.0   | 1410  | 1.7836          | 10.0151 | 63.778  |
| 2.0248        | 6.0   | 1692  | 1.7515          | 10.9865 | 62.224  |
| 2.0248        | 7.0   | 1974  | 1.7208          | 11.5089 | 61.2    |
| 1.9316        | 8.0   | 2256  | 1.6936          | 12.3755 | 60.1047 |
| 1.8584        | 9.0   | 2538  | 1.6731          | 12.8765 | 59.4427 |
| 1.8584        | 10.0  | 2820  | 1.6535          | 13.7278 | 57.6253 |
| 1.7949        | 11.0  | 3102  | 1.6360          | 14.2498 | 56.3913 |
| 1.7949        | 12.0  | 3384  | 1.6222          | 14.8795 | 55.346  |
| 1.7461        | 13.0  | 3666  | 1.6064          | 15.017  | 55.7473 |
| 1.7461        | 14.0  | 3948  | 1.5926          | 15.3093 | 56.0067 |
| 1.6998        | 15.0  | 4230  | 1.5803          | 15.6934 | 55.366  |
| 1.6635        | 16.0  | 4512  | 1.5707          | 16.3604 | 54.5413 |
| 1.6635        | 17.0  | 4794  | 1.5633          | 16.8086 | 53.824  |
| 1.621         | 18.0  | 5076  | 1.5515          | 17.1319 | 53.5927 |
| 1.621         | 19.0  | 5358  | 1.5450          | 17.5039 | 53.5167 |
| 1.6008        | 20.0  | 5640  | 1.5389          | 17.8012 | 53.6527 |
| 1.6008        | 21.0  | 5922  | 1.5314          | 17.7305 | 53.342  |
| 1.5656        | 22.0  | 6204  | 1.5259          | 18.1609 | 53.4033 |
| 1.5656        | 23.0  | 6486  | 1.5200          | 18.6506 | 52.226  |
| 1.5466        | 24.0  | 6768  | 1.5185          | 18.9433 | 52.2173 |
| 1.53          | 25.0  | 7050  | 1.5120          | 19.0978 | 52.022  |
| 1.53          | 26.0  | 7332  | 1.5083          | 19.1326 | 52.0527 |
| 1.5072        | 27.0  | 7614  | 1.5044          | 19.0854 | 52.2447 |
| 1.5072        | 28.0  | 7896  | 1.5002          | 19.372  | 51.7687 |
| 1.4926        | 29.0  | 8178  | 1.4977          | 19.5798 | 52.0327 |
| 1.4926        | 30.0  | 8460  | 1.4941          | 19.5161 | 51.9893 |
| 1.478         | 31.0  | 8742  | 1.4911          | 19.7821 | 51.534  |
| 1.47          | 32.0  | 9024  | 1.4897          | 19.7207 | 51.4787 |
| 1.47          | 33.0  | 9306  | 1.4888          | 19.8066 | 51.5407 |
| 1.4603        | 34.0  | 9588  | 1.4869          | 19.9036 | 51.398  |
| 1.4603        | 35.0  | 9870  | 1.4856          | 19.9575 | 51.352  |
| 1.4558        | 36.0  | 10152 | 1.4845          | 19.9513 | 51.4833 |
| 1.4558        | 37.0  | 10434 | 1.4840          | 20.0177 | 51.3027 |
| 1.4486        | 38.0  | 10716 | 1.4833          | 20.0644 | 51.484  |
| 1.4486        | 39.0  | 10998 | 1.4830          | 20.1001 | 51.5747 |
| 1.4452        | 40.0  | 11280 | 1.4830          | 20.1194 | 51.456  |


### Framework versions

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