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---
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
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