| | --- |
| | library_name: transformers |
| | 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: 1.8481 |
| | - Accuracy: 0.425 |
| | - F1: 0.4068 |
| | - Precision: 0.4371 |
| | - Recall: 0.425 |
| | - Mse: 5.314 |
| | - Mae: 1.37 |
| |
|
| | ## 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: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Mse | Mae | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:-----:| |
| | | 1.9914 | 1.0 | 157 | 1.7086 | 0.404 | 0.2561 | 0.3800 | 0.404 | 10.332 | 1.95 | |
| | | 1.5651 | 2.0 | 314 | 1.6295 | 0.419 | 0.3343 | 0.4048 | 0.419 | 7.397 | 1.591 | |
| | | 1.3878 | 3.0 | 471 | 1.6456 | 0.421 | 0.3666 | 0.4605 | 0.421 | 6.147 | 1.473 | |
| | | 1.1967 | 4.0 | 628 | 1.7054 | 0.42 | 0.3790 | 0.3598 | 0.42 | 5.874 | 1.44 | |
| | | 1.1002 | 5.0 | 785 | 1.7713 | 0.414 | 0.3896 | 0.3701 | 0.414 | 5.647 | 1.419 | |
| | | 0.9412 | 6.0 | 942 | 1.8481 | 0.425 | 0.4068 | 0.4371 | 0.425 | 5.314 | 1.37 | |
| | | 0.8737 | 7.0 | 1099 | 1.9534 | 0.407 | 0.4007 | 0.4025 | 0.407 | 5.141 | 1.375 | |
| | | 0.757 | 8.0 | 1256 | 2.0153 | 0.401 | 0.3932 | 0.3918 | 0.401 | 5.227 | 1.385 | |
| | | 0.6973 | 9.0 | 1413 | 2.0556 | 0.404 | 0.3979 | 0.4004 | 0.404 | 5.176 | 1.376 | |
| | | 0.6573 | 10.0 | 1570 | 2.0672 | 0.408 | 0.4008 | 0.4003 | 0.408 | 5.179 | 1.373 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.5.1+cu121 |
| | - Datasets 3.2.0 |
| | - Tokenizers 0.20.3 |
| |
|
