---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0410_lrate7.5b32
  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_lrate7.5b32

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: 0.4559
- Precisions: 0.8283
- Recall: 0.8004
- F-measure: 0.8131
- Accuracy: 0.9159

## 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: 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.2719        | 1.0   | 118  | 0.4068          | 0.8731     | 0.7017 | 0.7281    | 0.8921   |
| 0.2306        | 2.0   | 236  | 0.3380          | 0.7819     | 0.7690 | 0.7699    | 0.9017   |
| 0.1268        | 3.0   | 354  | 0.3740          | 0.7908     | 0.7845 | 0.7790    | 0.9060   |
| 0.0858        | 4.0   | 472  | 0.3834          | 0.7983     | 0.7651 | 0.7763    | 0.9092   |
| 0.0586        | 5.0   | 590  | 0.4200          | 0.8225     | 0.7933 | 0.8045    | 0.9094   |
| 0.0349        | 6.0   | 708  | 0.4474          | 0.8328     | 0.7926 | 0.8094    | 0.9107   |
| 0.0209        | 7.0   | 826  | 0.4559          | 0.8283     | 0.8004 | 0.8131    | 0.9159   |
| 0.013         | 8.0   | 944  | 0.4614          | 0.8175     | 0.8034 | 0.8097    | 0.9144   |


### Framework versions

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