---
license: mit
base_model: DTAI-KULeuven/robbert-2023-dutch-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: robbert2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# robbert2

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: 0.1668
- Accuracy: 0.9617
- F1: 0.6771
- Precision: 0.7418
- Recall: 0.6357

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1552        | 1.0   | 9646  | 0.1982          | 0.9569   | 0.4843 | 0.5375    | 0.4579 |
| 0.1169        | 2.0   | 19292 | 0.1856          | 0.9653   | 0.6065 | 0.7167    | 0.5540 |
| 0.0831        | 3.0   | 28938 | 0.1668          | 0.9617   | 0.6771 | 0.7418    | 0.6357 |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.19.1