| license: apache-2.0 | |
| base_model: bert-large-uncased | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| - precision | |
| - recall | |
| model-index: | |
| - name: bert-large-uncased | |
| 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. --> | |
| # bert-large-uncased | |
| This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.1397 | |
| - Accuracy: 0.6868 | |
| - F1: 0.6711 | |
| - Precision: 0.7266 | |
| - Recall: 0.6959 | |
| ## 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: 32 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_steps: 100 | |
| - num_epochs: 3 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | |
| | 1.9802 | 2.17 | 50 | 1.5449 | 0.5635 | 0.5166 | 0.5892 | 0.5801 | | |
| ### Framework versions | |
| - Transformers 4.37.2 | |
| - Pytorch 2.1.0+cu121 | |
| - Datasets 2.17.0 | |
| - Tokenizers 0.15.1 | |