---
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: 0.1457
- Precision: 0.5116
- Recall: 0.3964
- F1: 0.4467
- Accuracy: 0.9618

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1975        | 1.0   | 230  | 0.1641          | 0.6471    | 0.25   | 0.3607 | 0.9667   |
| 0.1939        | 2.0   | 460  | 0.1492          | 0.4912    | 0.3182 | 0.3862 | 0.9673   |
| 0.1543        | 3.0   | 690  | 0.1448          | 0.3103    | 0.3068 | 0.3086 | 0.9680   |
| 0.1571        | 4.0   | 920  | 0.1173          | 0.2105    | 0.1818 | 0.1951 | 0.9729   |
| 0.1401        | 5.0   | 1150 | 0.1095          | 0.3140    | 0.3068 | 0.3103 | 0.9732   |
| 0.1101        | 6.0   | 1380 | 0.1175          | 0.3896    | 0.3409 | 0.3636 | 0.9741   |
| 0.0639        | 7.0   | 1610 | 0.1138          | 0.3364    | 0.4091 | 0.3692 | 0.9707   |
| 0.0589        | 8.0   | 1840 | 0.1195          | 0.3838    | 0.4318 | 0.4064 | 0.9719   |


### Framework versions

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