---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0410_lrate5b16
  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. -->

# robbert0410_lrate5b16

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: 0.4327
- Precisions: 0.8044
- Recall: 0.7739
- F-measure: 0.7866
- Accuracy: 0.9059

## 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: 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6621        | 1.0   | 236  | 0.3874          | 0.8592     | 0.6840 | 0.6964    | 0.8788   |
| 0.3365        | 2.0   | 472  | 0.3512          | 0.8078     | 0.7402 | 0.7478    | 0.8916   |
| 0.2033        | 3.0   | 708  | 0.3476          | 0.8061     | 0.7621 | 0.7617    | 0.9055   |
| 0.132         | 4.0   | 944  | 0.3896          | 0.8035     | 0.7465 | 0.7632    | 0.9042   |
| 0.0793        | 5.0   | 1180 | 0.4327          | 0.8044     | 0.7739 | 0.7866    | 0.9059   |
| 0.0554        | 6.0   | 1416 | 0.4909          | 0.8386     | 0.7609 | 0.7774    | 0.9072   |
| 0.0378        | 7.0   | 1652 | 0.4867          | 0.7892     | 0.7651 | 0.7743    | 0.9070   |
| 0.0244        | 8.0   | 1888 | 0.5016          | 0.8046     | 0.7651 | 0.7756    | 0.9090   |


### Framework versions

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