---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: dbmdz/bert-base-turkish-cased
model-index:
- name: BERTurk_emotion_single
  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. -->

# BERTurk_emotion_single

This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4662
- Accuracy: 0.8795
- Precision: 0.8935
- Recall: 0.8795
- F1: 0.8757

## 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: 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 | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.4   | 50   | 1.5130          | 0.29     | 0.5337    | 0.29   | 0.1962 |
| No log        | 0.8   | 100  | 1.1556          | 0.665    | 0.5788    | 0.665  | 0.5841 |
| 0.952         | 1.2   | 150  | 0.8404          | 0.775    | 0.8279    | 0.775  | 0.7711 |
| 0.952         | 1.6   | 200  | 0.8298          | 0.795    | 0.8383    | 0.795  | 0.7817 |
| 0.1317        | 2.0   | 250  | 0.9024          | 0.77     | 0.8463    | 0.77   | 0.7493 |
| 0.1317        | 2.4   | 300  | 1.4757          | 0.715    | 0.8224    | 0.715  | 0.6780 |
| 0.1317        | 2.8   | 350  | 1.2916          | 0.765    | 0.8274    | 0.765  | 0.7429 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2