transformers pytorch bert text-classification generated_from_trainer base_model:dbmdz/bert-base-turkish-128k-cased license:mit autotrain_compatible endpoints_compatible region:us
---
license: mit
base_model: dbmdz/bert-base-turkish-128k-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-turkish-128k-cased-product-names
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-turkish-128k-cased-product-names

This model is a fine-tuned version of [dbmdz/bert-base-turkish-128k-cased](https://huggingface.co/dbmdz/bert-base-turkish-128k-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0667
- Accuracy: 0.9904

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 364  | 0.0598          | 0.9810   |
| 0.1386        | 2.0   | 728  | 0.0570          | 0.9872   |
| 0.056         | 3.0   | 1092 | 0.0594          | 0.9880   |
| 0.056         | 4.0   | 1456 | 0.0559          | 0.9896   |
| 0.0346        | 5.0   | 1820 | 0.0565          | 0.9892   |
| 0.0173        | 6.0   | 2184 | 0.0667          | 0.9904   |
| 0.0083        | 7.0   | 2548 | 0.0686          | 0.9894   |
| 0.0083        | 8.0   | 2912 | 0.0725          | 0.9894   |
| 0.0091        | 9.0   | 3276 | 0.0716          | 0.9902   |
| 0.0047        | 10.0  | 3640 | 0.0762          | 0.9894   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.13.3
