metadata
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: defect-classification-distilbert-baseline-25-epochs
results: []
defect-classification-distilbert-baseline-25-epochs
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2683
- Accuracy: 0.8834
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: 512
- eval_batch_size: 512
- 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: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6829 | 1.0 | 1062 | 0.5554 | 0.7841 |
| 0.4905 | 2.0 | 2124 | 0.4389 | 0.8172 |
| 0.4418 | 3.0 | 3186 | 0.3930 | 0.8379 |
| 0.4167 | 4.0 | 4248 | 0.3503 | 0.8491 |
| 0.4166 | 5.0 | 5310 | 0.3163 | 0.8612 |
| 0.4344 | 6.0 | 6372 | 0.3135 | 0.8638 |
| 0.3547 | 7.0 | 7434 | 0.3092 | 0.8648 |
| 0.4277 | 8.0 | 8496 | 0.3099 | 0.8633 |
| 0.399 | 9.0 | 9558 | 0.3071 | 0.8660 |
| 0.4125 | 10.0 | 10620 | 0.2843 | 0.8781 |
| 0.3662 | 11.0 | 11682 | 0.2899 | 0.8736 |
| 0.3396 | 12.0 | 12744 | 0.2796 | 0.8782 |
| 0.3775 | 13.0 | 13806 | 0.2797 | 0.8803 |
| 0.3552 | 14.0 | 14868 | 0.2757 | 0.8815 |
| 0.3208 | 15.0 | 15930 | 0.2747 | 0.8807 |
| 0.3344 | 16.0 | 16992 | 0.2702 | 0.8839 |
| 0.3171 | 17.0 | 18054 | 0.2745 | 0.8782 |
| 0.3535 | 18.0 | 19116 | 0.2745 | 0.8799 |
| 0.394 | 19.0 | 20178 | 0.2669 | 0.8866 |
| 0.299 | 20.0 | 21240 | 0.2720 | 0.8804 |
| 0.3209 | 21.0 | 22302 | 0.2720 | 0.8790 |
| 0.3366 | 22.0 | 23364 | 0.2696 | 0.8818 |
| 0.3531 | 23.0 | 24426 | 0.2690 | 0.8826 |
| 0.3368 | 24.0 | 25488 | 0.2685 | 0.8826 |
| 0.3251 | 25.0 | 26550 | 0.2683 | 0.8834 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0