| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: t5-base |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: t5-base-squad-qag-b |
| | 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-base-squad-qag-b |
| |
|
| | 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: 16.4900 |
| |
|
| | ## 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: 1e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 32 |
| | - optimizer: Use OptimizerNames.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: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 15.4767 | 0.5714 | 1 | 19.7375 | |
| | | 22.2253 | 1.5714 | 2 | 19.0585 | |
| | | 21.1788 | 2.5714 | 3 | 18.5133 | |
| | | 21.3016 | 3.5714 | 4 | 18.0134 | |
| | | 20.3052 | 4.5714 | 5 | 17.5808 | |
| | | 19.7086 | 5.5714 | 6 | 17.2109 | |
| | | 19.4675 | 6.5714 | 7 | 16.9223 | |
| | | 19.3453 | 7.5714 | 8 | 16.7059 | |
| | | 18.5491 | 8.5714 | 9 | 16.5610 | |
| | | 18.5816 | 9.5714 | 10 | 16.4900 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.48.3 |
| | - Pytorch 2.5.1+cu124 |
| | - Datasets 3.3.0 |
| | - Tokenizers 0.21.0 |
| | |
