--- license: apache-2.0 tags: - generated_from_trainer datasets: - glue metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-mrpc results: - task: name: Text Classification type: text-classification dataset: name: glue type: glue config: mrpc split: validation args: mrpc metrics: - name: Accuracy type: accuracy value: 0.8480392156862745 - name: F1 type: f1 value: 0.8945578231292517 --- # distilbert-base-uncased-finetuned-mrpc This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset. It achieves the following results on the evaluation set: - Loss: 0.4304 - Accuracy: 0.8480 - F1: 0.8946 ## 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | No log | 1.0 | 230 | 0.3851 | 0.8137 | 0.8652 | | No log | 2.0 | 460 | 0.3614 | 0.8456 | 0.8948 | | 0.4318 | 3.0 | 690 | 0.4304 | 0.8480 | 0.8946 | | 0.4318 | 4.0 | 920 | 0.5555 | 0.8407 | 0.8900 | | 0.1697 | 5.0 | 1150 | 0.5883 | 0.8456 | 0.8927 | ### Framework versions - Transformers 4.28.0 - Pytorch 2.0.1+cu118 - Datasets 2.12.0 - Tokenizers 0.13.3