---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: convberturk-keyword-extractor
  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. -->

# convberturk-keyword-extractor

This model is a fine-tuned version of [dbmdz/convbert-base-turkish-cased](https://huggingface.co/dbmdz/convbert-base-turkish-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4098
- Precision: 0.6742
- Recall: 0.7035
- Accuracy: 0.9175
- F1: 0.6886

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:--------:|:------:|
| 0.174         | 1.0   | 1875  | 0.1920          | 0.6546    | 0.6869 | 0.9184   | 0.6704 |
| 0.1253        | 2.0   | 3750  | 0.2030          | 0.6527    | 0.7317 | 0.9179   | 0.6900 |
| 0.091         | 3.0   | 5625  | 0.2517          | 0.6499    | 0.7473 | 0.9163   | 0.6952 |
| 0.0684        | 4.0   | 7500  | 0.2828          | 0.6633    | 0.7270 | 0.9167   | 0.6937 |
| 0.0536        | 5.0   | 9375  | 0.3307          | 0.6706    | 0.7194 | 0.9180   | 0.6942 |
| 0.0384        | 6.0   | 11250 | 0.3669          | 0.6655    | 0.7161 | 0.9157   | 0.6898 |
| 0.0316        | 7.0   | 13125 | 0.3870          | 0.6792    | 0.7002 | 0.9176   | 0.6895 |
| 0.0261        | 8.0   | 15000 | 0.4098          | 0.6742    | 0.7035 | 0.9175   | 0.6886 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1