---
library_name: transformers
license: mit
base_model: VRLLab/TurkishBERTweet
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: TurkishBERTweet_with_categories
  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. -->

# TurkishBERTweet_with_categories

This model is a fine-tuned version of [VRLLab/TurkishBERTweet](https://huggingface.co/VRLLab/TurkishBERTweet) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1821
- Precision: 0.2178
- Recall: 0.2136
- F1: 0.2157
- Accuracy: 0.9595

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2417        | 1.0   | 298  | 0.2246          | 0.1184    | 0.0874 | 0.1006 | 0.9489   |
| 0.1675        | 2.0   | 596  | 0.2198          | 0.18      | 0.1748 | 0.1773 | 0.9537   |
| 0.1071        | 3.0   | 894  | 0.2781          | 0.2703    | 0.1942 | 0.2260 | 0.9539   |
| 0.0622        | 4.0   | 1192 | 0.2997          | 0.1771    | 0.1650 | 0.1709 | 0.9504   |
| 0.0374        | 5.0   | 1490 | 0.3237          | 0.2785    | 0.2136 | 0.2418 | 0.9537   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0