| --- |
| 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 |
| - task: |
| type: natural-language-inference |
| name: Natural Language Inference |
| dataset: |
| name: glue |
| type: glue |
| config: mrpc |
| split: validation |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8774509803921569 |
| verified: true |
| - name: Precision |
| type: precision |
| value: 0.8803986710963455 |
| verified: true |
| - name: Recall |
| type: recall |
| value: 0.9498207885304659 |
| verified: true |
| - name: AUC |
| type: auc |
| value: 0.9474174099080325 |
| verified: true |
| - name: F1 |
| type: f1 |
| value: 0.9137931034482758 |
| verified: true |
| - name: loss |
| type: loss |
| value: 0.5562044978141785 |
| 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 |
|
|
