---
license: mit
base_model: dbmdz/bert-base-turkish-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: TTC4900Model
  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. -->

# TTC4900Model

This model is a fine-tuned version of [dbmdz/bert-base-turkish-uncased](https://huggingface.co/dbmdz/bert-base-turkish-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2304
- Accuracy: 0.9341
- F1: 0.8963
- Precision: 0.9000
- Recall: 0.8989

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 2.581         | 0.88  | 50   | 2.0974          | 0.4317   | 0.2930 | 0.4400    | 0.3556 |
| 1.3915        | 1.75  | 100  | 0.6175          | 0.8590   | 0.8144 | 0.8008    | 0.8445 |
| 0.3808        | 2.63  | 150  | 0.3171          | 0.8767   | 0.8481 | 0.9359    | 0.8620 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Tokenizers 0.15.0