| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-t5/t5-small |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: T5_small_fine_tuned |
| 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_fine_tuned |
| |
| 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: 2.6491 |
| - Rougel Fmeasure: 0.1247 |
| - Bertscore F1: -0.0215 |
| - Combined Score: 0.0516 |
| |
| ## 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 adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rougel Fmeasure | Bertscore F1 | Combined Score | |
| |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------------:| |
| | 1.9205 | 1.0 | 2369 | 2.6825 | 0.113 | -0.0448 | 0.0341 | |
| | 1.8233 | 2.0 | 4738 | 2.6561 | 0.1227 | -0.0249 | 0.0489 | |
| | 1.7693 | 3.0 | 7107 | 2.6505 | 0.1246 | -0.0215 | 0.0515 | |
| | 1.7611 | 4.0 | 9476 | 2.6491 | 0.1247 | -0.0215 | 0.0516 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.2 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
