| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - super_glue | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: T5_finetuned | |
| results: | |
| - task: | |
| name: Sequence-to-sequence Language Modeling | |
| type: text2text-generation | |
| dataset: | |
| name: super_glue | |
| type: super_glue | |
| config: boolq | |
| split: train | |
| args: boolq | |
| metrics: | |
| - name: Rouge1 | |
| type: rouge | |
| value: 79.3272 | |
| <!-- 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_finetuned | |
| This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the super_glue dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1077 | |
| - Rouge1: 79.3272 | |
| - Rouge2: 0.0 | |
| - Rougel: 79.2966 | |
| - Rougelsum: 79.3272 | |
| - Gen Len: 2.8269 | |
| ## 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: 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: 3 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| | |
| | 0.5134 | 1.0 | 590 | 0.1102 | 79.8165 | 0.0 | 79.8165 | 79.8471 | 2.7713 | | |
| | 0.105 | 2.0 | 1180 | 0.1049 | 80.3364 | 0.0 | 80.3364 | 80.367 | 2.6483 | | |
| | 0.1023 | 3.0 | 1770 | 0.1077 | 79.3272 | 0.0 | 79.2966 | 79.3272 | 2.8269 | | |
| ### Framework versions | |
| - Transformers 4.25.1 | |
| - Pytorch 1.13.0+cu116 | |
| - Datasets 2.8.0 | |
| - Tokenizers 0.13.2 | |