|
--- |
|
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: 0.9947 |
|
- Rouge1: 53.8834 |
|
- Rouge2: 35.147 |
|
- Rougel: 50.8217 |
|
- Rougelsum: 50.9105 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
|
| 2.0129 | 1.0 | 1531 | 1.5160 | 44.1037 | 21.8536 | 40.2425 | 40.3433 | |
|
| 1.6207 | 2.0 | 3062 | 1.2865 | 46.6327 | 25.2538 | 43.0594 | 43.1583 | |
|
| 1.4243 | 3.0 | 4593 | 1.2410 | 48.3304 | 27.729 | 45.0085 | 45.0977 | |
|
| 1.2828 | 4.0 | 6124 | 1.1008 | 50.7514 | 30.7978 | 47.5413 | 47.6432 | |
|
| 1.1796 | 5.0 | 7655 | 1.0646 | 52.4672 | 33.0679 | 49.2593 | 49.3381 | |
|
| 1.1059 | 6.0 | 9186 | 1.0082 | 53.4044 | 34.4035 | 50.3925 | 50.4943 | |
|
| 1.0596 | 7.0 | 10717 | 0.9947 | 53.8834 | 35.147 | 50.8217 | 50.9105 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.28.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
|
|