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---
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: 0.5696
- Accuracy: 0.69
- Auc: 0.714
- Precision: 0.722
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:---------:|
| 0.6689 | 1.0 | 21 | 0.6720 | 0.571 | 0.676 | 0.72 |
| 0.6684 | 2.0 | 42 | 0.5909 | 0.69 | 0.719 | 0.69 |
| 0.6279 | 3.0 | 63 | 0.6067 | 0.714 | 0.711 | 0.718 |
| 0.619 | 4.0 | 84 | 0.5969 | 0.714 | 0.711 | 0.73 |
| 0.6055 | 5.0 | 105 | 0.5809 | 0.714 | 0.708 | 0.718 |
| 0.5821 | 6.0 | 126 | 0.5729 | 0.714 | 0.714 | 0.718 |
| 0.5762 | 7.0 | 147 | 0.5921 | 0.667 | 0.708 | 0.727 |
| 0.5604 | 8.0 | 168 | 0.5659 | 0.714 | 0.716 | 0.73 |
| 0.5705 | 9.0 | 189 | 0.5659 | 0.69 | 0.714 | 0.722 |
| 0.571 | 10.0 | 210 | 0.5696 | 0.69 | 0.714 | 0.722 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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