| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - wikisql | |
| model-index: | |
| - name: T5Training | |
| 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. --> | |
| # T5Training | |
| This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the wikisql dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0341 | |
| - Rouge2 Precision: 0.9368 | |
| - Rouge2 Recall: 0.8687 | |
| - Rouge2 Fmeasure: 0.896 | |
| ## 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: 5e-05 | |
| - train_batch_size: 16 | |
| - eval_batch_size: 16 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 5 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | | |
| |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| | |
| | 0.0225 | 1.0 | 4049 | 0.0355 | 0.9325 | 0.8665 | 0.8929 | | |
| | 0.0182 | 2.0 | 8098 | 0.0359 | 0.9364 | 0.8682 | 0.8956 | | |
| | 0.016 | 3.0 | 12147 | 0.0354 | 0.9353 | 0.868 | 0.895 | | |
| | 0.0156 | 4.0 | 16196 | 0.0351 | 0.9366 | 0.8684 | 0.8958 | | |
| | 0.0177 | 5.0 | 20245 | 0.0341 | 0.9368 | 0.8687 | 0.896 | | |
| ### Framework versions | |
| - Transformers 4.26.0 | |
| - Pytorch 1.13.1+cu117 | |
| - Datasets 2.8.0 | |
| - Tokenizers 0.13.2 | |