|
|
--- |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- summarization |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: BBC |
|
|
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. --> |
|
|
|
|
|
# BBC |
|
|
|
|
|
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: 0.2824 |
|
|
- Rouge1: 18.46 |
|
|
- Rouge2: 17.0488 |
|
|
- Rougel: 18.3552 |
|
|
- Rougelsum: 18.3466 |
|
|
|
|
|
## 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: 4 |
|
|
- eval_batch_size: 4 |
|
|
- 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 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
|
|
| 0.7104 | 1.0 | 445 | 0.3218 | 17.4866 | 15.2567 | 17.0429 | 17.1216 | |
|
|
| 0.3433 | 2.0 | 890 | 0.3039 | 17.7632 | 15.8878 | 17.4551 | 17.5161 | |
|
|
| 0.3116 | 3.0 | 1335 | 0.2912 | 18.175 | 16.4391 | 17.9597 | 18.0081 | |
|
|
| 0.2908 | 4.0 | 1780 | 0.2869 | 18.2832 | 16.6726 | 18.1187 | 18.1205 | |
|
|
| 0.273 | 5.0 | 2225 | 0.2829 | 18.2807 | 16.7359 | 18.1496 | 18.1621 | |
|
|
| 0.2625 | 6.0 | 2670 | 0.2819 | 18.3845 | 16.8793 | 18.2622 | 18.2561 | |
|
|
| 0.2482 | 7.0 | 3115 | 0.2801 | 18.4748 | 17.0796 | 18.3792 | 18.3672 | |
|
|
| 0.2454 | 8.0 | 3560 | 0.2824 | 18.46 | 17.0488 | 18.3552 | 18.3466 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.25.1 |
|
|
- Pytorch 1.13.0+cu116 |
|
|
- Datasets 2.7.1 |
|
|
- Tokenizers 0.13.2 |
|
|
|
