|
--- |
|
license: apache-2.0 |
|
base_model: t5-base |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: t5-base-destination-inference |
|
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-destination-inference |
|
|
|
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0973 |
|
- Rouge1: 96.588 |
|
- Rouge2: 0.0 |
|
- Rougel: 96.588 |
|
- Rougelsum: 96.5792 |
|
|
|
## 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: 8 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
|
| 1.1906 | 1.0 | 5701 | 0.1466 | 94.1847 | 0.0 | 94.1672 | 94.1584 | |
|
| 0.9407 | 2.0 | 11402 | 0.1228 | 94.632 | 0.0 | 94.6408 | 94.632 | |
|
| 0.8533 | 3.0 | 17103 | 0.1106 | 95.4653 | 0.0 | 95.4653 | 95.4565 | |
|
| 0.7889 | 4.0 | 22804 | 0.1017 | 95.8337 | 0.0 | 95.8249 | 95.8162 | |
|
| 0.7394 | 5.0 | 28505 | 0.0990 | 96.2547 | 0.0 | 96.2591 | 96.2459 | |
|
| 0.7014 | 6.0 | 34206 | 0.0986 | 96.3951 | 0.0 | 96.4038 | 96.3863 | |
|
| 0.6737 | 7.0 | 39907 | 0.0966 | 96.4915 | 0.0 | 96.4872 | 96.474 | |
|
| 0.6533 | 8.0 | 45608 | 0.0973 | 96.588 | 0.0 | 96.588 | 96.5792 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.3 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|
