---
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-turkish-cased-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-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: 0.2877
- Accuracy: 0.9513

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 416  | 1.6794          | 0.7308   |
| 3.0588        | 2.0   | 832  | 0.7715          | 0.8660   |
| 0.9503        | 3.0   | 1248 | 0.5145          | 0.9026   |
| 0.4787        | 4.0   | 1664 | 0.3971          | 0.9243   |
| 0.2869        | 5.0   | 2080 | 0.3472          | 0.9285   |
| 0.2869        | 6.0   | 2496 | 0.3312          | 0.9345   |
| 0.1842        | 7.0   | 2912 | 0.3000          | 0.9393   |
| 0.1287        | 8.0   | 3328 | 0.2924          | 0.9447   |
| 0.0952        | 9.0   | 3744 | 0.2838          | 0.9471   |
| 0.0723        | 10.0  | 4160 | 0.2936          | 0.9489   |
| 0.0598        | 11.0  | 4576 | 0.2907          | 0.9495   |
| 0.0598        | 12.0  | 4992 | 0.2908          | 0.9507   |
| 0.0432        | 13.0  | 5408 | 0.2844          | 0.9495   |
| 0.0402        | 14.0  | 5824 | 0.2891          | 0.9507   |
| 0.031         | 15.0  | 6240 | 0.2877          | 0.9513   |


### Framework versions

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