| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| model-index: |
| - name: bert-practice-classifier |
| 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-practice-classifier |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7264 |
| - Accuracy: 0.375 |
| - Auc: 0.133 |
| - Precision: 0.333 |
|
|
| ## 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: 0.0002 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.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 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | Precision | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:---------:| |
| | 0.6963 | 1.0 | 4 | 0.7382 | 0.375 | 0.133 | 0.375 | |
| | 0.6877 | 2.0 | 8 | 0.7270 | 0.375 | 0.133 | 0.375 | |
| | 0.6984 | 3.0 | 12 | 0.7126 | 0.25 | 0.067 | 0.2 | |
| | 0.6871 | 4.0 | 16 | 0.7091 | 0.375 | 0.133 | 0.0 | |
| | 0.6912 | 5.0 | 20 | 0.7012 | 0.5 | 0.133 | 0.0 | |
| | 0.6867 | 6.0 | 24 | 0.7062 | 0.5 | 0.133 | 0.0 | |
| | 0.6862 | 7.0 | 28 | 0.7095 | 0.375 | 0.133 | 0.0 | |
| | 0.6639 | 8.0 | 32 | 0.7177 | 0.25 | 0.133 | 0.0 | |
| | 0.67 | 9.0 | 36 | 0.7239 | 0.125 | 0.133 | 0.0 | |
| | 0.6597 | 10.0 | 40 | 0.7264 | 0.375 | 0.133 | 0.333 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.50.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
|
|
