---
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: 0.6518
- Precisions: 0.8163
- Recall: 0.7936
- F-measure: 0.8017
- Accuracy: 0.9116

## 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: 2.5e-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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.62          | 1.0   | 942  | 0.4300          | 0.8644     | 0.6922 | 0.7030    | 0.8830   |
| 0.3475        | 2.0   | 1884 | 0.4044          | 0.8222     | 0.7322 | 0.7464    | 0.8970   |
| 0.2227        | 3.0   | 2826 | 0.4658          | 0.7715     | 0.7573 | 0.7476    | 0.9070   |
| 0.1488        | 4.0   | 3768 | 0.5292          | 0.8193     | 0.7461 | 0.7655    | 0.9045   |
| 0.0983        | 5.0   | 4710 | 0.5855          | 0.7938     | 0.7749 | 0.7829    | 0.9049   |
| 0.0652        | 6.0   | 5652 | 0.6155          | 0.8170     | 0.7826 | 0.7976    | 0.9100   |
| 0.0419        | 7.0   | 6594 | 0.6306          | 0.8072     | 0.7929 | 0.7971    | 0.9123   |
| 0.032         | 8.0   | 7536 | 0.6518          | 0.8163     | 0.7936 | 0.8017    | 0.9116   |


### Framework versions

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