| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - glue | |
| metrics: | |
| - accuracy | |
| - f1 | |
| base_model: bert-base-uncased | |
| model-index: | |
| - name: sequence_classification | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: glue | |
| type: glue | |
| args: mrpc | |
| metrics: | |
| - type: accuracy | |
| value: 0.8529411764705882 | |
| name: Accuracy | |
| - type: f1 | |
| value: 0.8943661971830987 | |
| name: F1 | |
| <!-- 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. --> | |
| # sequence_classification | |
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the glue dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.7738 | |
| - Accuracy: 0.8529 | |
| - F1: 0.8944 | |
| ## 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: 5e-05 | |
| - train_batch_size: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | |
| | No log | 1.0 | 459 | 0.3519 | 0.8627 | 0.9 | | |
| | 0.4872 | 2.0 | 918 | 0.6387 | 0.8333 | 0.8893 | | |
| | 0.2488 | 3.0 | 1377 | 0.7738 | 0.8529 | 0.8944 | | |
| ### Framework versions | |
| - Transformers 4.13.0.dev0 | |
| - Pytorch 1.10.0+cu102 | |
| - Datasets 1.15.1 | |
| - Tokenizers 0.10.3 | |