---
license: mit
base_model: dbmdz/distilbert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: acer_nitro_distilbert_turk
  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. -->

# acer_nitro_distilbert_turk

This model is a fine-tuned version of [dbmdz/distilbert-base-turkish-cased](https://huggingface.co/dbmdz/distilbert-base-turkish-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7724
- F1: 0.7596
- Roc Auc: 0.8506
- Accuracy: 0.6386

## 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: 2
- eval_batch_size: 2
- 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 | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 166  | 0.6408          | 0.7330 | 0.8464  | 0.5904   |
| No log        | 2.0   | 332  | 0.6674          | 0.7549 | 0.8434  | 0.6386   |
| No log        | 3.0   | 498  | 0.7058          | 0.7573 | 0.8470  | 0.6145   |
| 0.3537        | 4.0   | 664  | 0.7887          | 0.7333 | 0.8358  | 0.6145   |
| 0.3537        | 5.0   | 830  | 0.8267          | 0.7586 | 0.8447  | 0.6265   |
| 0.3537        | 6.0   | 996  | 0.7217          | 0.7477 | 0.8491  | 0.6506   |
| 0.191         | 7.0   | 1162 | 0.7180          | 0.7593 | 0.8588  | 0.6506   |
| 0.191         | 8.0   | 1328 | 0.7742          | 0.7670 | 0.8531  | 0.6386   |
| 0.191         | 9.0   | 1494 | 0.7798          | 0.7560 | 0.8493  | 0.6265   |
| 0.1294        | 10.0  | 1660 | 0.7724          | 0.7596 | 0.8506  | 0.6386   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0