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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-20-epochs
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. -->
# defect-classification-distilbert-baseline-20-epochs
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2853
- Accuracy: 0.8811
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6293 | 1.0 | 1062 | 0.5118 | 0.7980 |
| 0.5347 | 2.0 | 2124 | 0.3975 | 0.8323 |
| 0.4369 | 3.0 | 3186 | 0.3575 | 0.8526 |
| 0.4335 | 4.0 | 4248 | 0.3329 | 0.8627 |
| 0.4325 | 5.0 | 5310 | 0.3173 | 0.8693 |
| 0.4259 | 6.0 | 6372 | 0.3058 | 0.8763 |
| 0.35 | 7.0 | 7434 | 0.2999 | 0.8784 |
| 0.4424 | 8.0 | 8496 | 0.2985 | 0.8779 |
| 0.3915 | 9.0 | 9558 | 0.2987 | 0.8755 |
| 0.4196 | 10.0 | 10620 | 0.2942 | 0.8783 |
| 0.3827 | 11.0 | 11682 | 0.2936 | 0.8783 |
| 0.32 | 12.0 | 12744 | 0.2895 | 0.8806 |
| 0.3664 | 13.0 | 13806 | 0.2971 | 0.8737 |
| 0.3623 | 14.0 | 14868 | 0.2935 | 0.8760 |
| 0.3542 | 15.0 | 15930 | 0.2943 | 0.8745 |
| 0.3391 | 16.0 | 16992 | 0.2881 | 0.8810 |
| 0.3404 | 17.0 | 18054 | 0.2888 | 0.8783 |
| 0.3747 | 18.0 | 19116 | 0.2893 | 0.8776 |
| 0.38 | 19.0 | 20178 | 0.2856 | 0.8807 |
| 0.3123 | 20.0 | 21240 | 0.2853 | 0.8811 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|