---
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     |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1