---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert_testrun
  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_testrun

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: 0.5609
- Precisions: 0.8558
- Recall: 0.8234
- F-measure: 0.8375
- Accuracy: 0.9294

## 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: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4449        | 1.0   | 285  | 0.3985          | 0.8120     | 0.6963 | 0.7240    | 0.8907   |
| 0.19          | 2.0   | 570  | 0.3572          | 0.8522     | 0.7715 | 0.8031    | 0.9118   |
| 0.0946        | 3.0   | 855  | 0.3966          | 0.8331     | 0.7816 | 0.8013    | 0.9168   |
| 0.0492        | 4.0   | 1140 | 0.4321          | 0.8295     | 0.8127 | 0.8189    | 0.9187   |
| 0.034         | 5.0   | 1425 | 0.4523          | 0.8123     | 0.8122 | 0.8097    | 0.9241   |
| 0.0221        | 6.0   | 1710 | 0.5082          | 0.8111     | 0.8109 | 0.8097    | 0.9222   |
| 0.015         | 7.0   | 1995 | 0.5375          | 0.8587     | 0.7934 | 0.8194    | 0.9212   |
| 0.0121        | 8.0   | 2280 | 0.5233          | 0.8542     | 0.8256 | 0.8373    | 0.9292   |
| 0.0077        | 9.0   | 2565 | 0.5259          | 0.8277     | 0.8235 | 0.8246    | 0.9286   |
| 0.0063        | 10.0  | 2850 | 0.5609          | 0.8558     | 0.8234 | 0.8375    | 0.9294   |
| 0.003         | 11.0  | 3135 | 0.5672          | 0.8176     | 0.8197 | 0.8169    | 0.9271   |
| 0.002         | 12.0  | 3420 | 0.5968          | 0.8555     | 0.8184 | 0.8347    | 0.9294   |
| 0.0021        | 13.0  | 3705 | 0.5846          | 0.8315     | 0.8222 | 0.8263    | 0.9269   |
| 0.0016        | 14.0  | 3990 | 0.5905          | 0.8352     | 0.8167 | 0.8251    | 0.9263   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1