---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0510_lrate10b32
  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. -->

# robbert0510_lrate10b32

This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5022
- Precisions: 0.8217
- Recall: 0.7879
- F-measure: 0.8011
- Accuracy: 0.9168

## 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: 0.0001
- 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: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.625         | 1.0   | 118  | 0.4136          | 0.8611     | 0.6751 | 0.6866    | 0.8713   |
| 0.3164        | 2.0   | 236  | 0.3284          | 0.8110     | 0.7374 | 0.7474    | 0.8959   |
| 0.187         | 3.0   | 354  | 0.3490          | 0.7578     | 0.7662 | 0.7524    | 0.9060   |
| 0.1083        | 4.0   | 472  | 0.3738          | 0.8164     | 0.7748 | 0.7855    | 0.9120   |
| 0.0778        | 5.0   | 590  | 0.4234          | 0.7579     | 0.7677 | 0.7583    | 0.9042   |
| 0.0526        | 6.0   | 708  | 0.4802          | 0.8348     | 0.7556 | 0.7688    | 0.9049   |
| 0.0358        | 7.0   | 826  | 0.4723          | 0.8322     | 0.7671 | 0.7909    | 0.9107   |
| 0.023         | 8.0   | 944  | 0.4758          | 0.8024     | 0.7975 | 0.7973    | 0.9107   |
| 0.016         | 9.0   | 1062 | 0.5112          | 0.7991     | 0.7889 | 0.7917    | 0.9084   |
| 0.0117        | 10.0  | 1180 | 0.5022          | 0.8217     | 0.7879 | 0.8011    | 0.9168   |
| 0.0072        | 11.0  | 1298 | 0.5286          | 0.8190     | 0.7875 | 0.8009    | 0.9165   |
| 0.0052        | 12.0  | 1416 | 0.5207          | 0.8056     | 0.7929 | 0.7987    | 0.9135   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0