| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: summarization_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. --> |
| |
|
| | # summarization_model |
| | |
| | This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1359 |
| | - Rouge1: 0.1813 |
| | - Rouge2: 0.1114 |
| | - Rougel: 0.1616 |
| | - Rougelsum: 0.1617 |
| | - 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: 8 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | | 0.2358 | 1.0 | 1635 | 0.1719 | 0.1758 | 0.1033 | 0.1554 | 0.1554 | 19.0 | |
| | | 0.2043 | 2.0 | 3270 | 0.1574 | 0.1764 | 0.1046 | 0.1561 | 0.1561 | 19.0 | |
| | | 0.191 | 3.0 | 4905 | 0.1505 | 0.1778 | 0.1069 | 0.1577 | 0.1578 | 19.0 | |
| | | 0.178 | 4.0 | 6540 | 0.1448 | 0.1797 | 0.1093 | 0.1597 | 0.1597 | 19.0 | |
| | | 0.1734 | 5.0 | 8175 | 0.1406 | 0.1804 | 0.1102 | 0.1605 | 0.1604 | 19.0 | |
| | | 0.1681 | 6.0 | 9810 | 0.1376 | 0.1811 | 0.111 | 0.1613 | 0.1613 | 19.0 | |
| | | 0.1665 | 7.0 | 11445 | 0.1365 | 0.1815 | 0.1114 | 0.1618 | 0.1618 | 19.0 | |
| | | 0.1643 | 8.0 | 13080 | 0.1359 | 0.1813 | 0.1114 | 0.1616 | 0.1617 | 19.0 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.28.0 |
| | - Pytorch 2.0.0+cu118 |
| | - Datasets 2.11.0 |
| | - Tokenizers 0.13.3 |
| | |
