|
--- |
|
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: 1.4240 |
|
- Rouge1: 29.0369 |
|
- Rouge2: 0.0 |
|
- Rougel: 29.0007 |
|
- Rougelsum: 28.9826 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
|
| 2.1788 | 1.0 | 2762 | 1.6737 | 21.7686 | 0.0 | 21.7958 | 21.7596 | |
|
| 1.7176 | 2.0 | 5524 | 1.5569 | 24.6017 | 0.0 | 24.6017 | 24.5474 | |
|
| 1.556 | 3.0 | 8286 | 1.4978 | 26.05 | 0.0 | 26.05 | 26.0319 | |
|
| 1.4456 | 4.0 | 11048 | 1.4613 | 26.937 | 0.0 | 26.937 | 26.8827 | |
|
| 1.3661 | 5.0 | 13810 | 1.4351 | 28.2223 | 0.0 | 28.2223 | 28.2042 | |
|
| 1.3045 | 6.0 | 16572 | 1.4196 | 27.9508 | 0.0 | 27.9146 | 27.8965 | |
|
| 1.2519 | 7.0 | 19334 | 1.4211 | 28.8559 | 0.0 | 28.8378 | 28.8197 | |
|
| 1.2262 | 8.0 | 22096 | 1.4240 | 29.0369 | 0.0 | 29.0007 | 28.9826 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
