---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert_seed34_1311
  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. -->

# robbert_seed34_1311

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: 0.3777
- Precisions: 0.8501
- Recall: 0.8262
- F-measure: 0.8370
- Accuracy: 0.9450

## 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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 34
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4251        | 1.0   | 236  | 0.2557          | 0.7903     | 0.7339 | 0.7510    | 0.9248   |
| 0.2162        | 2.0   | 472  | 0.3018          | 0.8386     | 0.7336 | 0.7532    | 0.9200   |
| 0.1275        | 3.0   | 708  | 0.2461          | 0.8347     | 0.7758 | 0.7858    | 0.9364   |
| 0.0797        | 4.0   | 944  | 0.2773          | 0.8694     | 0.7843 | 0.8114    | 0.9383   |
| 0.049         | 5.0   | 1180 | 0.2767          | 0.8314     | 0.8143 | 0.8200    | 0.9419   |
| 0.03          | 6.0   | 1416 | 0.3036          | 0.8126     | 0.8106 | 0.8104    | 0.9407   |
| 0.0189        | 7.0   | 1652 | 0.3637          | 0.8051     | 0.8146 | 0.8073    | 0.9395   |
| 0.014         | 8.0   | 1888 | 0.3762          | 0.8479     | 0.7926 | 0.8135    | 0.9436   |
| 0.012         | 9.0   | 2124 | 0.3649          | 0.8486     | 0.8019 | 0.8205    | 0.9443   |
| 0.0045        | 10.0  | 2360 | 0.3966          | 0.8530     | 0.8000 | 0.8200    | 0.9431   |
| 0.0057        | 11.0  | 2596 | 0.3856          | 0.8564     | 0.8129 | 0.8307    | 0.9441   |
| 0.0054        | 12.0  | 2832 | 0.3777          | 0.8501     | 0.8262 | 0.8370    | 0.9450   |
| 0.0025        | 13.0  | 3068 | 0.3792          | 0.8608     | 0.8207 | 0.8369    | 0.9458   |
| 0.0019        | 14.0  | 3304 | 0.3859          | 0.8581     | 0.8149 | 0.8318    | 0.9455   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1