| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-bert/bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: intent_classfication2 |
| 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. --> |
|
|
| # intent_classfication2 |
| |
| This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1321 |
| - Accuracy: 0.9618 |
| |
| ## 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: 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: 15 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 1.6215 | 1.0 | 655 | 1.0384 | 0.8342 | |
| | 1.0518 | 2.0 | 1310 | 0.5333 | 0.8892 | |
| | 0.676 | 3.0 | 1965 | 0.3383 | 0.9228 | |
| | 0.3837 | 4.0 | 2620 | 0.2589 | 0.9373 | |
| | 0.3307 | 5.0 | 3275 | 0.2148 | 0.9415 | |
| | 0.2926 | 6.0 | 3930 | 0.1872 | 0.9492 | |
| | 0.2465 | 7.0 | 4585 | 0.1698 | 0.9530 | |
| | 0.2338 | 8.0 | 5240 | 0.1585 | 0.9553 | |
| | 0.2156 | 9.0 | 5895 | 0.1486 | 0.9599 | |
| | 0.2078 | 10.0 | 6550 | 0.1429 | 0.9603 | |
| | 0.2 | 11.0 | 7205 | 0.1392 | 0.9603 | |
| | 0.1973 | 12.0 | 7860 | 0.1362 | 0.9614 | |
| | 0.184 | 13.0 | 8515 | 0.1339 | 0.9622 | |
| | 0.1884 | 14.0 | 9170 | 0.1326 | 0.9622 | |
| | 0.1871 | 15.0 | 9825 | 0.1321 | 0.9618 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.47.0 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
| |
