---
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-15-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-15-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: 0.2980
- Accuracy: 0.8765

## 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: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7058        | 1.0   | 1062  | 0.6084          | 0.7927   |
| 0.5439        | 2.0   | 2124  | 0.4581          | 0.8141   |
| 0.4417        | 3.0   | 3186  | 0.3951          | 0.8403   |
| 0.4504        | 4.0   | 4248  | 0.3578          | 0.8487   |
| 0.428         | 5.0   | 5310  | 0.3352          | 0.8584   |
| 0.4089        | 6.0   | 6372  | 0.3347          | 0.8638   |
| 0.3428        | 7.0   | 7434  | 0.3248          | 0.8681   |
| 0.4219        | 8.0   | 8496  | 0.3178          | 0.8715   |
| 0.3689        | 9.0   | 9558  | 0.3044          | 0.8736   |
| 0.3891        | 10.0  | 10620 | 0.3037          | 0.8724   |
| 0.3849        | 11.0  | 11682 | 0.3064          | 0.8713   |
| 0.3302        | 12.0  | 12744 | 0.3006          | 0.8758   |
| 0.3576        | 13.0  | 13806 | 0.3016          | 0.8742   |
| 0.3548        | 14.0  | 14868 | 0.2990          | 0.8766   |
| 0.3596        | 15.0  | 15930 | 0.2980          | 0.8765   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0