|
--- |
|
license: apache-2.0 |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: t5-base-news_headlines |
|
results: [] |
|
--- |
|
|
|
<!-- 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-news_headlines |
|
|
|
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9975 |
|
- Rouge1: 53.7064 |
|
- Rouge2: 34.6278 |
|
- Rougel: 50.5129 |
|
- Rougelsum: 50.5108 |
|
|
|
## 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: 5.6e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 7 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
|
| 1.9933 | 1.0 | 1531 | 1.4942 | 44.2439 | 22.1239 | 40.5281 | 40.5525 | |
|
| 1.6029 | 2.0 | 3062 | 1.2824 | 46.5726 | 25.1122 | 43.131 | 43.151 | |
|
| 1.409 | 3.0 | 4593 | 1.2358 | 48.3188 | 27.7403 | 44.9576 | 45.0009 | |
|
| 1.2699 | 4.0 | 6124 | 1.1600 | 50.9858 | 30.6655 | 47.775 | 47.8414 | |
|
| 1.1696 | 5.0 | 7655 | 1.0607 | 52.2212 | 32.6952 | 49.0023 | 49.0812 | |
|
| 1.0934 | 6.0 | 9186 | 1.0173 | 53.1629 | 33.9552 | 49.9629 | 50.0118 | |
|
| 1.049 | 7.0 | 10717 | 0.9975 | 53.7064 | 34.6278 | 50.5129 | 50.5108 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.28.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
|
|
