| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: t5_small_SA |
| 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_SA |
|
|
| This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6247 |
| - Rouge1: 0.18 |
| - Rouge2: 0.0618 |
| - Rougel: 0.1699 |
| - Rougelsum: 0.1685 |
| - Gen Len: 9.9558 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## 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: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 12 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | 0.646 | 1.0 | 527 | 0.6675 | 0.1451 | 0.0366 | 0.1367 | 0.138 | 9.0619 | |
| | 0.6271 | 2.0 | 1054 | 0.6543 | 0.1579 | 0.0431 | 0.1482 | 0.1499 | 10.2832 | |
| | 0.6412 | 3.0 | 1581 | 0.6484 | 0.1501 | 0.039 | 0.1454 | 0.147 | 9.3805 | |
| | 0.6172 | 4.0 | 2108 | 0.6400 | 0.1607 | 0.0507 | 0.1543 | 0.1554 | 10.3363 | |
| | 0.6314 | 5.0 | 2635 | 0.6366 | 0.181 | 0.0599 | 0.1737 | 0.1739 | 9.6549 | |
| | 0.6152 | 6.0 | 3162 | 0.6344 | 0.1739 | 0.0637 | 0.1676 | 0.1666 | 9.0265 | |
| | 0.5835 | 7.0 | 3689 | 0.6324 | 0.1753 | 0.0596 | 0.1685 | 0.1673 | 9.2478 | |
| | 0.5852 | 8.0 | 4216 | 0.6277 | 0.1839 | 0.0614 | 0.1768 | 0.1755 | 10.0265 | |
| | 0.6129 | 9.0 | 4743 | 0.6260 | 0.1801 | 0.0617 | 0.171 | 0.1704 | 9.9115 | |
| | 0.5848 | 10.0 | 5270 | 0.6256 | 0.1743 | 0.0557 | 0.1624 | 0.1611 | 10.1593 | |
| | 0.5993 | 11.0 | 5797 | 0.6247 | 0.1748 | 0.06 | 0.167 | 0.1646 | 10.1504 | |
| | 0.5479 | 12.0 | 6324 | 0.6247 | 0.18 | 0.0618 | 0.1699 | 0.1685 | 9.9558 | |
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| ### Framework versions |
|
|
| - Transformers 4.26.1 |
| - Pytorch 1.13.1+cu116 |
| - Datasets 2.10.1 |
| - Tokenizers 0.13.2 |
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|
