---
library_name: transformers
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0961
- F1: 0.9870
- Accuracy: 0.9903
- F1 Yes: 0.9805

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy | F1 Yes |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:------:|
| 0.4447        | 1.0   | 567  | 0.1354          | 0.9645 | 0.9740   | 0.9461 |
| 0.5017        | 2.0   | 1134 | 0.1364          | 0.9709 | 0.9788   | 0.9558 |
| 0.3631        | 3.0   | 1701 | 0.0939          | 0.9821 | 0.9868   | 0.9730 |
| 0.1957        | 4.0   | 2268 | 0.1017          | 0.9827 | 0.9872   | 0.9739 |
| 0.2480        | 5.0   | 2835 | 0.1281          | 0.9832 | 0.9876   | 0.9746 |
| 0.0166        | 6.0   | 3402 | 0.1206          | 0.9851 | 0.9890   | 0.9775 |
| 0.0452        | 7.0   | 3969 | 0.1049          | 0.9881 | 0.9912   | 0.9821 |
| 0.0261        | 8.0   | 4536 | 0.1177          | 0.9857 | 0.9894   | 0.9784 |
| 0.0004        | 9.0   | 5103 | 0.1145          | 0.9869 | 0.9903   | 0.9803 |


### Framework versions

- Transformers 5.2.0
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2