---
license: mit
base_model: DTAI-KULeuven/robbert-2023-dutch-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: robbert-2023-dutch-base-gender
  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. -->

# robbert-2023-dutch-base-gender

This model is a fine-tuned version of [DTAI-KULeuven/robbert-2023-dutch-base](https://huggingface.co/DTAI-KULeuven/robbert-2023-dutch-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6591
- Precision: 0.6282
- Recall: 0.6290
- Fscore: 0.6278
- Accuracy: 0.6285

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Fscore | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.616         | 0.29  | 2000 | 0.6498          | 0.6295    | 0.6299 | 0.6266 | 0.6267   |
| 0.6033        | 0.59  | 4000 | 0.6584          | 0.6278    | 0.6274 | 0.6228 | 0.6228   |
| 0.5896        | 0.88  | 6000 | 0.6600          | 0.6285    | 0.6293 | 0.6282 | 0.6290   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.5
- Tokenizers 0.15.0