--- language: - en license: apache-2.0 tags: - generated_from_trainer datasets: - glue metrics: - accuracy - f1 model-index: - name: testing results: - task: name: Text Classification type: text-classification dataset: name: GLUE MRPC type: glue args: mrpc metrics: - name: Accuracy type: accuracy value: 0.6813725490196079 - name: F1 type: f1 value: 0.8104956268221574 --- # testing This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE MRPC dataset. It achieves the following results on the evaluation set: - Loss: 0.6644 - Accuracy: 0.6814 - F1: 0.8105 - Combined Score: 0.7459 ## 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: 1 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 10 ### Training results ### Framework versions - Transformers 4.11.0.dev0 - Pytorch 1.9.0+cu111 - Datasets 1.11.0 - Tokenizers 0.10.3