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

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: 0.1263
- Precision: 0.8113
- Recall: 0.6244
- F1: 0.7057
- Accuracy: 0.9640

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1849        | 1.0   | 230  | 0.1457          | 0.9188    | 0.6041 | 0.7289 | 0.9706   |
| 0.1753        | 2.0   | 460  | 0.1303          | 0.9158    | 0.6447 | 0.7567 | 0.9730   |
| 0.1333        | 3.0   | 690  | 0.1369          | 0.9158    | 0.6447 | 0.7567 | 0.9730   |
| 0.123         | 4.0   | 920  | 0.1316          | 0.9439    | 0.7020 | 0.8051 | 0.9773   |
| 0.0913        | 5.0   | 1150 | 0.1188          | 0.8717    | 0.7518 | 0.8073 | 0.9768   |
| 0.0733        | 6.0   | 1380 | 0.1372          | 0.9440    | 0.7443 | 0.8323 | 0.9800   |
| 0.0359        | 7.0   | 1610 | 0.1484          | 0.8975    | 0.7251 | 0.8021 | 0.9768   |
| 0.0339        | 8.0   | 1840 | 0.1595          | 0.8887    | 0.7704 | 0.8253 | 0.9787   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0