---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0410_lrate2.5b4
  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_lrate2.5b4

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: 0.6503
- Precisions: 0.8243
- Recall: 0.7775
- F-measure: 0.7978
- Accuracy: 0.9076

## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6524        | 1.0   | 942  | 0.4534          | 0.8361     | 0.6745 | 0.6791    | 0.8712   |
| 0.372         | 2.0   | 1884 | 0.4010          | 0.7997     | 0.7323 | 0.7446    | 0.8930   |
| 0.23          | 3.0   | 2826 | 0.4862          | 0.7950     | 0.7439 | 0.7519    | 0.8963   |
| 0.1446        | 4.0   | 3768 | 0.5515          | 0.8251     | 0.7729 | 0.7851    | 0.9080   |
| 0.0916        | 5.0   | 4710 | 0.6213          | 0.7940     | 0.7793 | 0.7849    | 0.9036   |
| 0.0597        | 6.0   | 5652 | 0.6503          | 0.8243     | 0.7775 | 0.7978    | 0.9076   |
| 0.0317        | 7.0   | 6594 | 0.6706          | 0.8098     | 0.7824 | 0.7922    | 0.9107   |
| 0.021         | 8.0   | 7536 | 0.6690          | 0.8172     | 0.7847 | 0.7968    | 0.9135   |


### Framework versions

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