---
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
datasets:
- wmt14
metrics:
- bleu
model-index:
- name: T5_base_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: 8.5002
---

<!-- 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_wmt14_En_Fr_1million

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the wmt14 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9945
- Bleu: 8.5002
- Gen Len: 18.0143

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 0.9735        | 1.0   | 1667  | 1.1059          | 9.3433 | 17.994  |
| 0.8671        | 2.0   | 3334  | 1.1192          | 9.3551 | 18.008  |
| 0.7975        | 3.0   | 5001  | 1.1509          | 9.4297 | 17.996  |
| 0.737         | 4.0   | 6668  | 1.1819          | 9.0739 | 18.0223 |
| 0.6746        | 5.0   | 8335  | 1.2076          | 9.1258 | 17.9873 |
| 0.6314        | 6.0   | 10002 | 1.2640          | 9.1364 | 18.0207 |
| 0.5833        | 7.0   | 11669 | 1.2948          | 8.8072 | 17.9907 |
| 0.5349        | 8.0   | 13336 | 1.3525          | 8.8513 | 17.9867 |
| 0.5025        | 9.0   | 15003 | 1.4087          | 8.7599 | 18.0027 |
| 0.4614        | 10.0  | 16670 | 1.4562          | 8.6011 | 18.015  |
| 0.4227        | 11.0  | 18337 | 1.5169          | 8.6315 | 18.018  |
| 0.3938        | 12.0  | 20004 | 1.5842          | 8.6045 | 18.0133 |
| 0.358         | 13.0  | 21671 | 1.6334          | 8.459  | 17.9997 |
| 0.3271        | 14.0  | 23338 | 1.6989          | 8.4979 | 17.9937 |
| 0.3056        | 15.0  | 25005 | 1.7529          | 8.5421 | 18.0357 |
| 0.278         | 16.0  | 26672 | 1.8151          | 8.3963 | 18.0027 |
| 0.2548        | 17.0  | 28339 | 1.8812          | 8.3497 | 18.0193 |
| 0.238         | 18.0  | 30006 | 1.9249          | 8.4306 | 18.0227 |
| 0.223         | 19.0  | 31673 | 1.9742          | 8.5156 | 18.013  |
| 0.2112        | 20.0  | 33340 | 1.9945          | 8.5002 | 18.0143 |


### Framework versions

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