| language: | |
| - en | |
| license: mit | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - glue | |
| metrics: | |
| - accuracy | |
| - f1 | |
| model-index: | |
| - name: roberta-base-mrpc | |
| results: | |
| - task: | |
| name: Text Classification | |
| type: text-classification | |
| dataset: | |
| name: GLUE MRPC | |
| type: glue | |
| args: mrpc | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.8774509803921569 | |
| - name: F1 | |
| type: f1 | |
| value: 0.9137931034482758 | |
| - task: | |
| type: natural-language-inference | |
| name: Natural Language Inference | |
| dataset: | |
| name: glue | |
| type: glue | |
| config: mrpc | |
| split: train | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.979825517993457 | |
| verified: true | |
| - name: Precision | |
| type: precision | |
| value: 0.9842615012106537 | |
| verified: true | |
| - name: Recall | |
| type: recall | |
| value: 0.9858528698464026 | |
| verified: true | |
| - name: AUC | |
| type: auc | |
| value: 0.9958293217637636 | |
| verified: true | |
| - name: F1 | |
| type: f1 | |
| value: 0.9850565428109854 | |
| verified: true | |
| - name: loss | |
| type: loss | |
| value: 0.08004990220069885 | |
| verified: true | |
| <!-- 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. --> | |
| # roberta-base-mrpc | |
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the GLUE MRPC dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.5565 | |
| - Accuracy: 0.8775 | |
| - F1: 0.9138 | |
| - Combined Score: 0.8956 | |
| ## 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: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 5.0 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.18.0 | |
| - Pytorch 1.10.0+cu102 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.11.6 | |