---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
datasets:
- wmt14
metrics:
- bleu
model-index:
- name: T5_wmt14_En_Fr_1million
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: wmt14
      type: wmt14
      config: fr-en
      split: validation
      args: fr-en
    metrics:
    - name: Bleu
      type: bleu
      value: 8.7934
---

<!-- 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_wmt14_En_Fr_1million

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co./google-t5/t5-small) on the wmt14 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3618
- Bleu: 8.7934
- Gen Len: 17.9953

## 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: 0.001
- train_batch_size: 60
- eval_batch_size: 60
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 1.0796        | 1.0   | 1667  | 1.1872          | 9.2959 | 18.0253 |
| 1.01          | 2.0   | 3334  | 1.2029          | 9.1594 | 18.0187 |
| 0.9686        | 3.0   | 5001  | 1.2114          | 9.2836 | 18.0123 |
| 0.9366        | 4.0   | 6668  | 1.2261          | 9.18   | 17.995  |
| 0.8999        | 5.0   | 8335  | 1.2319          | 9.2754 | 17.9793 |
| 0.8769        | 6.0   | 10002 | 1.2413          | 9.1705 | 18.026  |
| 0.8536        | 7.0   | 11669 | 1.2502          | 9.036  | 17.9987 |
| 0.8273        | 8.0   | 13336 | 1.2633          | 9.2003 | 18.006  |
| 0.8125        | 9.0   | 15003 | 1.2740          | 9.0991 | 18.009  |
| 0.7905        | 10.0  | 16670 | 1.2835          | 8.9005 | 18.007  |
| 0.774         | 11.0  | 18337 | 1.2943          | 9.0676 | 17.9967 |
| 0.76          | 12.0  | 20004 | 1.3023          | 9.0644 | 18.0227 |
| 0.7358        | 13.0  | 21671 | 1.3125          | 8.9858 | 18.0027 |
| 0.7238        | 14.0  | 23338 | 1.3204          | 9.0178 | 18.0073 |
| 0.7143        | 15.0  | 25005 | 1.3317          | 8.9826 | 18.015  |
| 0.6988        | 16.0  | 26672 | 1.3402          | 8.9224 | 18.0073 |
| 0.6829        | 17.0  | 28339 | 1.3500          | 8.9307 | 17.996  |
| 0.6776        | 18.0  | 30006 | 1.3517          | 8.8798 | 17.9987 |
| 0.6695        | 19.0  | 31673 | 1.3585          | 8.895  | 17.9967 |
| 0.6637        | 20.0  | 33340 | 1.3618          | 8.7934 | 17.9953 |


### Framework versions

- Transformers 4.32.1
- Pytorch 1.12.1
- Datasets 2.18.0
- Tokenizers 0.13.2