|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: google-t5/t5-small |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: my_billsum_model |
|
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. --> |
|
|
|
# my_billsum_model |
|
|
|
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: 2.3699 |
|
- Rouge1: 0.1958 |
|
- Rouge2: 0.0949 |
|
- Rougel: 0.167 |
|
- Rougelsum: 0.167 |
|
- 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: 2e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
| No log | 1.0 | 62 | 2.7958 | 0.1228 | 0.0386 | 0.0997 | 0.1 | 19.0 | |
|
| No log | 2.0 | 124 | 2.5846 | 0.1385 | 0.047 | 0.1139 | 0.114 | 19.0 | |
|
| No log | 3.0 | 186 | 2.5034 | 0.1506 | 0.0563 | 0.1232 | 0.1234 | 19.0 | |
|
| No log | 4.0 | 248 | 2.4548 | 0.1734 | 0.0756 | 0.1467 | 0.1468 | 19.0 | |
|
| No log | 5.0 | 310 | 2.4231 | 0.1893 | 0.0877 | 0.1597 | 0.1597 | 19.0 | |
|
| No log | 6.0 | 372 | 2.3991 | 0.1926 | 0.0913 | 0.1638 | 0.1638 | 19.0 | |
|
| No log | 7.0 | 434 | 2.3862 | 0.1945 | 0.0944 | 0.166 | 0.166 | 19.0 | |
|
| No log | 8.0 | 496 | 2.3764 | 0.195 | 0.094 | 0.1662 | 0.1663 | 19.0 | |
|
| 2.7718 | 9.0 | 558 | 2.3714 | 0.1959 | 0.0952 | 0.1672 | 0.1672 | 19.0 | |
|
| 2.7718 | 10.0 | 620 | 2.3699 | 0.1958 | 0.0949 | 0.167 | 0.167 | 19.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.1+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
