---
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: 0.1966
- Precision: 0.4301
- Recall: 0.3604
- F1: 0.3922
- Accuracy: 0.9591

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1734        | 1.0   | 230  | 0.1177          | 0.1495    | 0.1818 | 0.1641 | 0.9667   |
| 0.1235        | 2.0   | 460  | 0.1159          | 0.4394    | 0.3295 | 0.3766 | 0.9699   |
| 0.0779        | 3.0   | 690  | 0.1331          | 0.3483    | 0.3523 | 0.3503 | 0.9715   |
| 0.0564        | 4.0   | 920  | 0.1152          | 0.4286    | 0.375  | 0.4000 | 0.9756   |
| 0.0302        | 5.0   | 1150 | 0.1620          | 0.3830    | 0.4091 | 0.3956 | 0.9722   |
| 0.0226        | 6.0   | 1380 | 0.1654          | 0.3786    | 0.4432 | 0.4084 | 0.9749   |
| 0.0087        | 7.0   | 1610 | 0.1906          | 0.4875    | 0.4432 | 0.4643 | 0.9750   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3