|
--- |
|
license: apache-2.0 |
|
base_model: google/mt5-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: mt5_deed_sum |
|
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. --> |
|
|
|
# mt5_deed_sum |
|
|
|
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co./google/mt5-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5590 |
|
- Rouge1: 0.0 |
|
- Rouge2: 0.0 |
|
- Rougel: 0.0 |
|
- Rougelsum: 0.0 |
|
- Gen Len: 19.0 |
|
|
|
## 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: 5e-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 |
|
- lr_scheduler_warmup_steps: 5000 |
|
- num_epochs: 25 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
| 19.6644 | 1.0 | 188 | 13.7553 | 0.7175 | 0.0 | 0.7387 | 0.7032 | 12.283 | |
|
| 10.6133 | 2.0 | 376 | 11.3168 | 0.7175 | 0.0 | 0.7387 | 0.7032 | 13.4654 | |
|
| 10.1742 | 3.0 | 564 | 7.7772 | 0.7175 | 0.0 | 0.7387 | 0.7032 | 15.9874 | |
|
| 2.8326 | 4.0 | 752 | 4.6011 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 19.0 | |
|
| 4.2099 | 5.0 | 940 | 5.8284 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 15.8805 | |
|
| 1.7867 | 6.0 | 1128 | 2.0588 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 15.761 | |
|
| 3.6568 | 7.0 | 1316 | 1.7242 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 12.9371 | |
|
| 4.1534 | 8.0 | 1504 | 1.4302 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 15.1761 | |
|
| 0.9298 | 9.0 | 1692 | 1.3871 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 14.3711 | |
|
| 1.5429 | 10.0 | 1880 | 1.1574 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 18.4969 | |
|
| 1.1307 | 11.0 | 2068 | 1.0076 | 0.8804 | 0.1144 | 0.8573 | 0.8336 | 19.0 | |
|
| 0.9566 | 12.0 | 2256 | 0.9130 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 19.0 | |
|
| 0.6761 | 13.0 | 2444 | 0.8454 | 0.8804 | 0.1144 | 0.8573 | 0.8336 | 19.0 | |
|
| 0.1983 | 14.0 | 2632 | 0.7835 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | |
|
| 0.5771 | 15.0 | 2820 | 0.7411 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | |
|
| 1.1574 | 16.0 | 3008 | 0.7099 | 0.3594 | 0.2648 | 0.3594 | 0.3594 | 19.0 | |
|
| 0.1504 | 17.0 | 3196 | 0.6689 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | |
|
| 0.1265 | 18.0 | 3384 | 0.6576 | 0.3594 | 0.2648 | 0.3594 | 0.3594 | 19.0 | |
|
| 0.6688 | 19.0 | 3572 | 0.6355 | 0.3594 | 0.2648 | 0.3594 | 0.3594 | 19.0 | |
|
| 0.1103 | 20.0 | 3760 | 0.6101 | 0.5391 | 0.3972 | 0.5391 | 0.5391 | 19.0 | |
|
| 0.4472 | 21.0 | 3948 | 0.6018 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | |
|
| 0.0696 | 22.0 | 4136 | 0.5804 | 0.2459 | 0.1324 | 0.2459 | 0.2223 | 19.0 | |
|
| 0.2857 | 23.0 | 4324 | 0.5685 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | |
|
| 0.4744 | 24.0 | 4512 | 0.5475 | 0.2459 | 0.1324 | 0.2459 | 0.2223 | 19.0 | |
|
| 0.2841 | 25.0 | 4700 | 0.5590 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.1.0.dev20230811+cu121 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.15.2 |
|
|
