---
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-turkish-cased-stopword-product-names-classification
  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. -->

# bert-base-turkish-cased-stopword-product-names-classification

This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3536
- Accuracy: 0.948

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 313  | 2.2729          | 0.5744   |
| 3.0971        | 2.0   | 626  | 1.0825          | 0.8184   |
| 3.0971        | 3.0   | 939  | 0.7240          | 0.8616   |
| 0.9848        | 4.0   | 1252 | 0.5729          | 0.8776   |
| 0.4744        | 5.0   | 1565 | 0.4712          | 0.8944   |
| 0.4744        | 6.0   | 1878 | 0.4396          | 0.9024   |
| 0.2716        | 7.0   | 2191 | 0.3794          | 0.9176   |
| 0.1782        | 8.0   | 2504 | 0.3714          | 0.932    |
| 0.1782        | 9.0   | 2817 | 0.3588          | 0.928    |
| 0.1104        | 10.0  | 3130 | 0.3214          | 0.9384   |
| 0.1104        | 11.0  | 3443 | 0.3391          | 0.9376   |
| 0.0843        | 12.0  | 3756 | 0.3376          | 0.9408   |
| 0.0616        | 13.0  | 4069 | 0.3470          | 0.9384   |
| 0.0616        | 14.0  | 4382 | 0.3525          | 0.9336   |
| 0.0384        | 15.0  | 4695 | 0.3335          | 0.9368   |
| 0.033         | 16.0  | 5008 | 0.3334          | 0.9424   |
| 0.033         | 17.0  | 5321 | 0.3490          | 0.94     |
| 0.0246        | 18.0  | 5634 | 0.3260          | 0.944    |
| 0.0246        | 19.0  | 5947 | 0.3482          | 0.9408   |
| 0.0173        | 20.0  | 6260 | 0.3482          | 0.9456   |
| 0.0138        | 21.0  | 6573 | 0.3446          | 0.9448   |
| 0.0138        | 22.0  | 6886 | 0.3578          | 0.944    |
| 0.008         | 23.0  | 7199 | 0.3415          | 0.9464   |
| 0.007         | 24.0  | 7512 | 0.3536          | 0.948    |
| 0.007         | 25.0  | 7825 | 0.3667          | 0.948    |
| 0.0069        | 26.0  | 8138 | 0.3605          | 0.9464   |
| 0.0069        | 27.0  | 8451 | 0.3652          | 0.9456   |
| 0.0053        | 28.0  | 8764 | 0.3650          | 0.9472   |
| 0.0043        | 29.0  | 9077 | 0.3623          | 0.9472   |
| 0.0043        | 30.0  | 9390 | 0.3635          | 0.9472   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3