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

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: 0.3919
- Accuracy: 0.859
- Precision: 0.8671
- Recall: 0.859
- F1: 0.8541

## 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   | 1.6478          | 0.23     | 0.0529    | 0.23   | 0.0860 |
| No log        | 0.8   | 100  | 0.6822          | 0.77     | 0.8494    | 0.77   | 0.7556 |
| 1.163         | 1.2   | 150  | 0.7381          | 0.745    | 0.7713    | 0.745  | 0.7431 |
| 1.163         | 1.6   | 200  | 1.2519          | 0.75     | 0.8436    | 0.75   | 0.7028 |
| 0.1426        | 2.0   | 250  | 1.2671          | 0.72     | 0.7730    | 0.72   | 0.6964 |


### Framework versions

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