--- language: - en license: apache-2.0 tags: - generated_from_trainer datasets: - nyu-mll/glue metrics: - accuracy - f1 model-index: - name: mrpc results: - task: type: text-classification name: Text Classification dataset: name: GLUE MRPC type: glue args: mrpc metrics: - type: accuracy value: 0.8823529411764706 name: Accuracy - type: f1 value: 0.9180887372013652 name: F1 --- # mrpc This model is a fine-tuned version of [bert-large-uncased-whole-word-masking](https://huggingface.co/bert-large-uncased-whole-word-masking) on the GLUE MRPC dataset. It achieves the following results on the evaluation set: - Loss: 0.3680 - Accuracy: 0.8824 - F1: 0.9181 - Combined Score: 0.9002 ## 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: 3e-05 - train_batch_size: 32 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06 - lr_scheduler_type: linear - num_epochs: 3.0 ### Training results ### Framework versions - Transformers 4.18.0 - Pytorch 1.10.0a0+gitfe03f8c - Datasets 2.1.0 - Tokenizers 0.12.1