---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- ccmatrix
metrics:
- bleu
model-index:
- name: t5-small-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: 13.5927
---

<!-- 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-it-to-en

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: 2.4066
- Bleu: 13.5927
- Gen Len: 28.6473

## 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   | 2.9032          | 7.2452  | 35.1327 |
| 3.2663        | 2.0   | 564   | 2.8156          | 8.3336  | 31.2673 |
| 3.2663        | 3.0   | 846   | 2.7615          | 9.1403  | 30.248  |
| 3.0467        | 4.0   | 1128  | 2.7211          | 9.2676  | 30.2893 |
| 3.0467        | 5.0   | 1410  | 2.6872          | 9.5597  | 30.4067 |
| 2.9575        | 6.0   | 1692  | 2.6600          | 9.907   | 30.3153 |
| 2.9575        | 7.0   | 1974  | 2.6361          | 10.2292 | 29.902  |
| 2.8814        | 8.0   | 2256  | 2.6132          | 10.4384 | 30.1187 |
| 2.8284        | 9.0   | 2538  | 2.5930          | 10.572  | 30.0447 |
| 2.8284        | 10.0  | 2820  | 2.5774          | 10.9557 | 29.5547 |
| 2.7827        | 11.0  | 3102  | 2.5604          | 11.1435 | 29.5847 |
| 2.7827        | 12.0  | 3384  | 2.5484          | 11.4067 | 29.4807 |
| 2.7496        | 13.0  | 3666  | 2.5342          | 11.569  | 29.5827 |
| 2.7496        | 14.0  | 3948  | 2.5208          | 11.7581 | 30.07   |
| 2.7094        | 15.0  | 4230  | 2.5105          | 11.9629 | 29.6993 |
| 2.6764        | 16.0  | 4512  | 2.5007          | 12.2675 | 29.1    |
| 2.6764        | 17.0  | 4794  | 2.4916          | 12.2227 | 29.4    |
| 2.6516        | 18.0  | 5076  | 2.4817          | 12.3529 | 29.222  |
| 2.6516        | 19.0  | 5358  | 2.4747          | 12.6053 | 29.036  |
| 2.6271        | 20.0  | 5640  | 2.4672          | 12.6659 | 29.0993 |
| 2.6271        | 21.0  | 5922  | 2.4602          | 12.8286 | 29.2087 |
| 2.602         | 22.0  | 6204  | 2.4546          | 12.8915 | 29.0233 |
| 2.602         | 23.0  | 6486  | 2.4486          | 12.7892 | 29.2173 |
| 2.5922        | 24.0  | 6768  | 2.4438          | 12.8928 | 29.042  |
| 2.5781        | 25.0  | 7050  | 2.4386          | 13.1954 | 28.8607 |
| 2.5781        | 26.0  | 7332  | 2.4341          | 13.0077 | 28.8367 |
| 2.5578        | 27.0  | 7614  | 2.4306          | 13.1084 | 28.7487 |
| 2.5578        | 28.0  | 7896  | 2.4258          | 13.0929 | 28.9067 |
| 2.5477        | 29.0  | 8178  | 2.4236          | 13.2008 | 28.966  |
| 2.5477        | 30.0  | 8460  | 2.4203          | 13.3476 | 28.7133 |
| 2.5331        | 31.0  | 8742  | 2.4170          | 13.3539 | 28.8787 |
| 2.5312        | 32.0  | 9024  | 2.4148          | 13.3781 | 28.742  |
| 2.5312        | 33.0  | 9306  | 2.4130          | 13.3425 | 28.8393 |
| 2.5234        | 34.0  | 9588  | 2.4113          | 13.4549 | 28.732  |
| 2.5234        | 35.0  | 9870  | 2.4099          | 13.5228 | 28.8313 |
| 2.5131        | 36.0  | 10152 | 2.4084          | 13.547  | 28.6733 |
| 2.5131        | 37.0  | 10434 | 2.4076          | 13.6099 | 28.5193 |
| 2.5101        | 38.0  | 10716 | 2.4071          | 13.5853 | 28.64   |
| 2.5101        | 39.0  | 10998 | 2.4067          | 13.572  | 28.6687 |
| 2.5136        | 40.0  | 11280 | 2.4066          | 13.5927 | 28.6473 |


### Framework versions

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