| license: mit | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - super_glue | |
| metrics: | |
| - accuracy | |
| base_model: microsoft/deberta-v3-base | |
| model-index: | |
| - name: yes_no_qna_deberta_model | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: super_glue | |
| type: super_glue | |
| config: boolq | |
| split: train | |
| args: boolq | |
| metrics: | |
| - type: accuracy | |
| value: 0.8507645259938837 | |
| name: Accuracy | |
| <!-- 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. --> | |
| # yes_no_qna_deberta_model | |
| This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the super_glue dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.5570 | |
| - Accuracy: 0.8508 | |
| ## 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 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 0.583 | 1.0 | 590 | 0.4086 | 0.8251 | | |
| | 0.348 | 2.0 | 1180 | 0.4170 | 0.8465 | | |
| | 0.2183 | 3.0 | 1770 | 0.5570 | 0.8508 | | |
| ### Framework versions | |
| - Transformers 4.25.1 | |
| - Pytorch 1.13.0+cu116 | |
| - Datasets 2.8.0 | |
| - Tokenizers 0.13.2 | |