|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: google-t5/t5-small |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: t5-small-finetuned-amazon-en |
|
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-small-finetuned-amazon-en |
|
|
|
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.6372 |
|
- Rouge1: 23.1675 |
|
- Rouge2: 13.593 |
|
- Rougel: 22.2169 |
|
- Rougelsum: 22.3275 |
|
|
|
## 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: 128 |
|
- eval_batch_size: 128 |
|
- seed: 42 |
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- num_epochs: 8 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
|
| 2.8706 | 1.0 | 79 | 2.7303 | 22.6649 | 13.1507 | 21.6996 | 21.8226 | |
|
| 2.8591 | 2.0 | 158 | 2.6905 | 22.819 | 13.2646 | 21.8821 | 21.9906 | |
|
| 2.8214 | 3.0 | 237 | 2.6750 | 22.8648 | 13.3025 | 21.931 | 22.0772 | |
|
| 2.7875 | 4.0 | 316 | 2.6564 | 22.8115 | 13.2944 | 21.874 | 22.0061 | |
|
| 2.779 | 5.0 | 395 | 2.6451 | 23.0489 | 13.5043 | 22.0878 | 22.2228 | |
|
| 2.763 | 6.0 | 474 | 2.6435 | 23.0105 | 13.4214 | 22.0635 | 22.1647 | |
|
| 2.7413 | 7.0 | 553 | 2.6385 | 23.1595 | 13.6131 | 22.2155 | 22.3352 | |
|
| 2.7443 | 8.0 | 632 | 2.6372 | 23.1675 | 13.593 | 22.2169 | 22.3275 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.48.0 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
