| --- |
| license: apache-2.0 |
| base_model: google-t5/t5-small |
| 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 [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: 1.5805 |
| - Rouge1: 0.1786 |
| - Rouge2: 0.0576 |
| - Rougel: 0.1488 |
| - Rougelsum: 0.148 |
| - Gen Len: 18.5642 |
| |
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | No log | 1.0 | 377 | 1.6488 | 0.1711 | 0.0545 | 0.1441 | 0.1445 | 18.5134 | |
| | 1.851 | 2.0 | 754 | 1.6059 | 0.1743 | 0.0565 | 0.1478 | 0.1477 | 18.5134 | |
| | 1.7899 | 3.0 | 1131 | 1.5859 | 0.1758 | 0.0575 | 0.1463 | 0.1459 | 18.5433 | |
| | 1.7524 | 4.0 | 1508 | 1.5805 | 0.1786 | 0.0576 | 0.1488 | 0.148 | 18.5642 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.41.2 |
| - Pytorch 2.1.2 |
| - Datasets 2.19.2 |
| - Tokenizers 0.19.1 |
| |
