|
--- |
|
license: apache-2.0 |
|
base_model: t5-small |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- eur-lex-sum |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: T5_small_eurlexsum |
|
results: |
|
- task: |
|
name: Sequence-to-sequence Language Modeling |
|
type: text2text-generation |
|
dataset: |
|
name: eur-lex-sum |
|
type: eur-lex-sum |
|
config: french |
|
split: test |
|
args: french |
|
metrics: |
|
- name: Rouge1 |
|
type: rouge |
|
value: 0.2288 |
|
--- |
|
|
|
<!-- 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_eurlexsum |
|
|
|
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the eur-lex-sum dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9360 |
|
- Rouge1: 0.2288 |
|
- Rouge2: 0.1816 |
|
- Rougel: 0.2157 |
|
- Rougelsum: 0.2158 |
|
- Gen Len: 19.0 |
|
|
|
## 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: 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: 8 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
| No log | 1.0 | 71 | 1.4482 | 0.1743 | 0.0982 | 0.1509 | 0.1511 | 19.0 | |
|
| No log | 2.0 | 142 | 1.1661 | 0.193 | 0.1257 | 0.1731 | 0.1734 | 19.0 | |
|
| No log | 3.0 | 213 | 1.0651 | 0.2072 | 0.1483 | 0.1892 | 0.1896 | 19.0 | |
|
| No log | 4.0 | 284 | 1.0053 | 0.2167 | 0.1638 | 0.2017 | 0.2019 | 19.0 | |
|
| No log | 5.0 | 355 | 0.9706 | 0.222 | 0.1731 | 0.2082 | 0.2079 | 19.0 | |
|
| No log | 6.0 | 426 | 0.9510 | 0.2253 | 0.1771 | 0.2114 | 0.2114 | 19.0 | |
|
| No log | 7.0 | 497 | 0.9393 | 0.2263 | 0.1785 | 0.2134 | 0.2133 | 19.0 | |
|
| 1.4549 | 8.0 | 568 | 0.9360 | 0.2288 | 0.1816 | 0.2157 | 0.2158 | 19.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.13.1 |
|
- Tokenizers 0.13.3 |
|
|
