|
|
--- |
|
|
license: apache-2.0 |
|
|
base_model: t5-small |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- xsum |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: xsum-t5-small |
|
|
results: |
|
|
- task: |
|
|
name: Sequence-to-sequence Language Modeling |
|
|
type: text2text-generation |
|
|
dataset: |
|
|
name: xsum |
|
|
type: xsum |
|
|
config: default |
|
|
split: validation |
|
|
args: default |
|
|
metrics: |
|
|
- name: Rouge1 |
|
|
type: rouge |
|
|
value: 28.3309 |
|
|
--- |
|
|
|
|
|
<!-- 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. --> |
|
|
|
|
|
# xsum-t5-small |
|
|
|
|
|
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 2.4789 |
|
|
- Rouge1: 28.3309 |
|
|
- Rouge2: 7.7568 |
|
|
- Rougel: 22.2948 |
|
|
- Rougelsum: 22.2942 |
|
|
- Gen Len: 18.824 |
|
|
|
|
|
## 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: 1 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| |
|
|
| 2.9158 | 0.16 | 2000 | 2.5725 | 26.6629 | 6.6436 | 20.8032 | 20.7995 | 18.7886 | |
|
|
| 2.7868 | 0.31 | 4000 | 2.5286 | 27.3979 | 7.1077 | 21.4451 | 21.4487 | 18.8045 | |
|
|
| 2.756 | 0.47 | 6000 | 2.5058 | 27.8049 | 7.4383 | 21.8465 | 21.8479 | 18.8179 | |
|
|
| 2.7388 | 0.63 | 8000 | 2.4903 | 28.1541 | 7.6412 | 22.1566 | 22.1572 | 18.8265 | |
|
|
| 2.7208 | 0.78 | 10000 | 2.4819 | 28.2559 | 7.6877 | 22.2086 | 22.2118 | 18.8268 | |
|
|
| 2.7175 | 0.94 | 12000 | 2.4789 | 28.3309 | 7.7568 | 22.2948 | 22.2942 | 18.824 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.33.3 |
|
|
- Pytorch 2.0.1+cu118 |
|
|
- Datasets 2.14.5 |
|
|
- Tokenizers 0.13.3 |
|
|
|
