---
license: mit
base_model: burakaytan/roberta-base-turkish-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: laptop_kriter
  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. -->

# laptop_kriter

This model is a fine-tuned version of [burakaytan/roberta-base-turkish-uncased](https://huggingface.co/burakaytan/roberta-base-turkish-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2151
- F1: 0.7709
- Roc Auc: 0.8574
- Accuracy: 0.7344

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.3066        | 1.0   | 1151  | 0.2457          | 0.5688 | 0.7257  | 0.6484   |
| 0.2325        | 2.0   | 2302  | 0.2088          | 0.6630 | 0.7908  | 0.6719   |
| 0.1723        | 3.0   | 3453  | 0.2023          | 0.6933 | 0.8174  | 0.6875   |
| 0.159         | 4.0   | 4604  | 0.2004          | 0.7312 | 0.8363  | 0.7188   |
| 0.1306        | 5.0   | 5755  | 0.2138          | 0.7168 | 0.8104  | 0.7148   |
| 0.1034        | 6.0   | 6906  | 0.2103          | 0.7745 | 0.8641  | 0.7539   |
| 0.0865        | 7.0   | 8057  | 0.2107          | 0.7684 | 0.8530  | 0.75     |
| 0.0733        | 8.0   | 9208  | 0.2099          | 0.7757 | 0.8663  | 0.7383   |
| 0.0643        | 9.0   | 10359 | 0.2130          | 0.7772 | 0.8586  | 0.7539   |
| 0.0617        | 10.0  | 11510 | 0.2151          | 0.7709 | 0.8574  | 0.7344   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0