| --- |
| license: apache-2.0 |
| tags: |
| - summarization |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: BBC |
| 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. --> |
|
|
| # BBC |
|
|
| This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2824 |
| - Rouge1: 18.46 |
| - Rouge2: 17.0488 |
| - Rougel: 18.3552 |
| - Rougelsum: 18.3466 |
|
|
| ## 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: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 8 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
| | 0.7104 | 1.0 | 445 | 0.3218 | 17.4866 | 15.2567 | 17.0429 | 17.1216 | |
| | 0.3433 | 2.0 | 890 | 0.3039 | 17.7632 | 15.8878 | 17.4551 | 17.5161 | |
| | 0.3116 | 3.0 | 1335 | 0.2912 | 18.175 | 16.4391 | 17.9597 | 18.0081 | |
| | 0.2908 | 4.0 | 1780 | 0.2869 | 18.2832 | 16.6726 | 18.1187 | 18.1205 | |
| | 0.273 | 5.0 | 2225 | 0.2829 | 18.2807 | 16.7359 | 18.1496 | 18.1621 | |
| | 0.2625 | 6.0 | 2670 | 0.2819 | 18.3845 | 16.8793 | 18.2622 | 18.2561 | |
| | 0.2482 | 7.0 | 3115 | 0.2801 | 18.4748 | 17.0796 | 18.3792 | 18.3672 | |
| | 0.2454 | 8.0 | 3560 | 0.2824 | 18.46 | 17.0488 | 18.3552 | 18.3466 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.25.1 |
| - Pytorch 1.13.0+cu116 |
| - Datasets 2.7.1 |
| - Tokenizers 0.13.2 |
|
|
