| license: apache-2.0 | |
| base_model: bert-base-uncased | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| - precision | |
| - recall | |
| model-index: | |
| - name: results | |
| results: [] | |
| <!-- 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. --> | |
| # results | |
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.5341 | |
| - Accuracy: 0.8650 | |
| - F1: 0.8653 | |
| - Precision: 0.8661 | |
| - Recall: 0.8650 | |
| ## 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: 16 | |
| - eval_batch_size: 64 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_steps: 500 | |
| - num_epochs: 4 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | |
| | 0.4791 | 1.0 | 246 | 0.5719 | 0.7483 | 0.7541 | 0.8107 | 0.7483 | | |
| | 0.4459 | 2.0 | 492 | 0.4187 | 0.8467 | 0.8486 | 0.8608 | 0.8467 | | |
| | 0.1932 | 3.0 | 738 | 0.4394 | 0.8581 | 0.8590 | 0.8611 | 0.8581 | | |
| | 0.181 | 4.0 | 984 | 0.5341 | 0.8650 | 0.8653 | 0.8661 | 0.8650 | | |
| ### Framework versions | |
| - Transformers 4.36.0 | |
| - Pytorch 2.0.0 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.15.0 | |