|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- wmt16 |
|
metrics: |
|
- bleu |
|
model-index: |
|
- name: t5-small-finetuned-en-to-ro-lr_2e-3-fp_false |
|
results: |
|
- task: |
|
name: Sequence-to-sequence Language Modeling |
|
type: text2text-generation |
|
dataset: |
|
name: wmt16 |
|
type: wmt16 |
|
args: ro-en |
|
metrics: |
|
- name: Bleu |
|
type: bleu |
|
value: 7.1921 |
|
--- |
|
|
|
<!-- 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-en-to-ro-lr_2e-3-fp_false |
|
|
|
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wmt16 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.4239 |
|
- Bleu: 7.1921 |
|
- Gen Len: 18.2611 |
|
|
|
## 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: 0.002 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:| |
|
| 0.8922 | 0.05 | 2000 | 1.7000 | 6.5274 | 18.2656 | |
|
| 0.8621 | 0.1 | 4000 | 1.6409 | 6.6411 | 18.2311 | |
|
| 0.8433 | 0.16 | 6000 | 1.6396 | 6.6601 | 18.2596 | |
|
| 0.8297 | 0.21 | 8000 | 1.6304 | 6.7129 | 18.2581 | |
|
| 0.8006 | 0.26 | 10000 | 1.6022 | 6.6067 | 18.2816 | |
|
| 0.793 | 0.31 | 12000 | 1.5999 | 6.551 | 18.2631 | |
|
| 0.774 | 0.37 | 14000 | 1.5586 | 6.7105 | 18.2661 | |
|
| 0.7618 | 0.42 | 16000 | 1.5769 | 6.7278 | 18.2526 | |
|
| 0.7463 | 0.47 | 18000 | 1.5625 | 6.6972 | 18.2201 | |
|
| 0.7394 | 0.52 | 20000 | 1.5377 | 6.936 | 18.2491 | |
|
| 0.7203 | 0.58 | 22000 | 1.5191 | 7.0205 | 18.2731 | |
|
| 0.7158 | 0.63 | 24000 | 1.5055 | 6.835 | 18.2506 | |
|
| 0.688 | 0.68 | 26000 | 1.4779 | 7.0534 | 18.2716 | |
|
| 0.678 | 0.73 | 28000 | 1.4691 | 6.9735 | 18.2616 | |
|
| 0.6677 | 0.79 | 30000 | 1.4702 | 7.0359 | 18.2496 | |
|
| 0.6568 | 0.84 | 32000 | 1.4534 | 6.9982 | 18.2556 | |
|
| 0.6475 | 0.89 | 34000 | 1.4427 | 7.0443 | 18.2466 | |
|
| 0.6395 | 0.94 | 36000 | 1.4265 | 7.1205 | 18.2721 | |
|
| 0.6319 | 1.0 | 38000 | 1.4239 | 7.1921 | 18.2611 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.12.5 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 1.16.1 |
|
- Tokenizers 0.10.3 |
|
|
