---
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: 0.5271
- Precision: 0.4533
- Recall: 0.4378
- F1: 0.4454
- Accuracy: 0.8407

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7102        | 1.0   | 105  | 0.5722          | 0.6       | 0.1720 | 0.2673 | 0.8499   |
| 0.4812        | 2.0   | 210  | 0.4792          | 0.5023    | 0.3439 | 0.4083 | 0.8645   |
| 0.3025        | 3.0   | 315  | 0.5154          | 0.3987    | 0.4013 | 0.4    | 0.8523   |
| 0.1848        | 4.0   | 420  | 0.6540          | 0.4181    | 0.5446 | 0.4730 | 0.8327   |
| 0.1135        | 5.0   | 525  | 0.6031          | 0.4959    | 0.5828 | 0.5359 | 0.8587   |


### Framework versions

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