| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: t5-small |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: t5-summarizer-fast |
| 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-summarizer-fast |
|
|
| 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: 1.0230 |
| - Rouge1: 0.0369 |
| - Rouge2: 0.0176 |
| - Rougel: 0.031 |
| - Rougelsum: 0.0312 |
|
|
| ## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | No log | 1.0 | 225 | 1.0963 | 0.0 | 0.0 | 0.0 | 0.0 | |
| | No log | 2.0 | 450 | 1.0365 | 0.0116 | 0.0044 | 0.0092 | 0.0095 | |
| | 1.9999 | 3.0 | 675 | 1.0230 | 0.0369 | 0.0176 | 0.031 | 0.0312 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
