--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-mrpc results: [] --- # distilbert-base-uncased-finetuned-mrpc This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5682 - Accuracy: 0.7164 - F1: 0.2022 ## 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: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| | 0.5789 | 1.0 | 635 | 0.5764 | 0.7055 | 0.0 | | 0.543 | 2.0 | 1270 | 0.5682 | 0.7164 | 0.2022 | | 0.4661 | 3.0 | 1905 | 0.6358 | 0.7164 | 0.2812 | | 0.2338 | 4.0 | 2540 | 0.9347 | 0.6844 | 0.4670 | | 0.1538 | 5.0 | 3175 | 1.3556 | 0.6758 | 0.4740 | | 0.1067 | 6.0 | 3810 | 1.6163 | 0.7016 | 0.3322 | | 0.0928 | 7.0 | 4445 | 2.0786 | 0.6984 | 0.3609 | | 0.0438 | 8.0 | 5080 | 2.1976 | 0.6945 | 0.4309 | | 0.0312 | 9.0 | 5715 | 2.1931 | 0.6969 | 0.4209 | | 0.0311 | 10.0 | 6350 | 2.4030 | 0.6883 | 0.4158 | | 0.0281 | 11.0 | 6985 | 2.3715 | 0.7148 | 0.3739 | | 0.0166 | 12.0 | 7620 | 2.6843 | 0.6984 | 0.3390 | | 0.0167 | 13.0 | 8255 | 2.7291 | 0.6922 | 0.3604 | | 0.0181 | 14.0 | 8890 | 2.7929 | 0.6906 | 0.3851 | | 0.0147 | 15.0 | 9525 | 2.8976 | 0.7117 | 0.3303 | | 0.0103 | 16.0 | 10160 | 3.0229 | 0.6859 | 0.3964 | | 0.0047 | 17.0 | 10795 | 3.0616 | 0.6836 | 0.3817 | | 0.0136 | 18.0 | 11430 | 3.0513 | 0.6875 | 0.3730 | | 0.005 | 19.0 | 12065 | 3.0634 | 0.6930 | 0.3732 | | 0.0042 | 20.0 | 12700 | 3.0611 | 0.7 | 0.3642 | ### Framework versions - Transformers 4.28.1 - Pytorch 2.0.1+cu117 - Datasets 1.18.4 - Tokenizers 0.12.1