---
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: []
---

<!-- 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-25-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: 0.2683
- 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