metadata
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: []
bert-practice-classifier
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5532
- Accuracy: 0.762
- Auc: 0.662
- Precision: 0.789
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 |
|---|---|---|---|---|---|---|
| 0.6737 | 1.0 | 21 | 0.6780 | 0.571 | 0.625 | 0.818 |
| 0.673 | 2.0 | 42 | 0.5509 | 0.762 | 0.688 | 0.762 |
| 0.6283 | 3.0 | 63 | 0.5884 | 0.714 | 0.65 | 0.75 |
| 0.621 | 4.0 | 84 | 0.5868 | 0.762 | 0.65 | 0.789 |
| 0.6016 | 5.0 | 105 | 0.5632 | 0.762 | 0.65 | 0.789 |
| 0.5837 | 6.0 | 126 | 0.5434 | 0.714 | 0.662 | 0.75 |
| 0.5671 | 7.0 | 147 | 0.5921 | 0.667 | 0.662 | 0.765 |
| 0.5686 | 8.0 | 168 | 0.5448 | 0.762 | 0.675 | 0.789 |
| 0.5659 | 9.0 | 189 | 0.5459 | 0.762 | 0.662 | 0.789 |
| 0.5747 | 10.0 | 210 | 0.5532 | 0.762 | 0.662 | 0.789 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0