---
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-10-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-10-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: 0.2976
- Accuracy: 0.8762

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6008        | 1.0   | 1062  | 0.5867          | 0.7578   |
| 0.4986        | 2.0   | 2124  | 0.4298          | 0.8051   |
| 0.4322        | 3.0   | 3186  | 0.3786          | 0.8255   |
| 0.458         | 4.0   | 4248  | 0.3425          | 0.8462   |
| 0.4143        | 5.0   | 5310  | 0.3274          | 0.8533   |
| 0.4443        | 6.0   | 6372  | 0.3153          | 0.8620   |
| 0.3508        | 7.0   | 7434  | 0.3076          | 0.8691   |
| 0.4489        | 8.0   | 8496  | 0.2989          | 0.8745   |
| 0.364         | 9.0   | 9558  | 0.2974          | 0.8764   |
| 0.4091        | 10.0  | 10620 | 0.2976          | 0.8762   |


### Framework versions

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