---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: req_mod_ner_modelv2
  results: []
widget:
- text: "De Oplossing ondersteunt het zoeken op de metadata van zaken, documenten en objecten en op gegevens uit de basisregistraties die gekoppeld zijn aan een zaak."
- text: "De Oplossing ondersteunt parafering en het plaatsen van een gecertificeerde elektronische handtekening."
- text: "De Aangeboden oplossing stelt de medewerker in staat een zaak te registreren."
- text: "Het Financieel systeem heeft functionaliteit om een debiteurenadministratie te voeren."
- text: "Als gebruiker wil ik dat de oplossing mij naar zaken laat zoeken op basis van zaaknummer, zaaktitel, omschrijving en datum."
---

<!-- 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. -->

# req_mod_ner_modelv2

This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-ner](https://huggingface.co/pdelobelle/robbert-v2-dutch-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6678
- Precision: 0.7090
- Recall: 0.7701
- F1: 0.7383
- Accuracy: 0.9261

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16

### Evaluation results

| Validation Loss | Precision | Recall | F1     | Accuracy |
|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6678          | 0.7090    | 0.7701 | 0.7383 | 0.9261   |


### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 240  | 0.4780          | 0.3456    | 0.4052 | 0.3730 | 0.8789   |
| No log        | 2.0   | 480  | 0.3903          | 0.5934    | 0.4655 | 0.5217 | 0.9080   |
| 0.4168        | 3.0   | 720  | 0.5082          | 0.6782    | 0.5086 | 0.5813 | 0.9169   |
| 0.4168        | 4.0   | 960  | 0.4307          | 0.5846    | 0.6552 | 0.6179 | 0.9201   |
| 0.1633        | 5.0   | 1200 | 0.5179          | 0.6       | 0.5948 | 0.5974 | 0.9233   |
| 0.1633        | 6.0   | 1440 | 0.6073          | 0.5752    | 0.5603 | 0.5677 | 0.9185   |
| 0.0676        | 7.0   | 1680 | 0.6198          | 0.6638    | 0.6638 | 0.6638 | 0.9233   |
| 0.0676        | 8.0   | 1920 | 0.6876          | 0.6311    | 0.6638 | 0.6471 | 0.9185   |
| 0.0445        | 9.0   | 2160 | 0.7112          | 0.6522    | 0.6466 | 0.6494 | 0.9201   |
| 0.0445        | 10.0  | 2400 | 0.7232          | 0.6522    | 0.6466 | 0.6494 | 0.9193   |
| 0.0259        | 11.0  | 2640 | 0.6511          | 0.6371    | 0.6810 | 0.6583 | 0.9233   |
| 0.0259        | 12.0  | 2880 | 0.6733          | 0.6783    | 0.6724 | 0.6753 | 0.9257   |
| 0.0146        | 13.0  | 3120 | 0.6636          | 0.6695    | 0.6810 | 0.6752 | 0.9282   |
| 0.0146        | 14.0  | 3360 | 0.6943          | 0.6496    | 0.6552 | 0.6524 | 0.9257   |
| 0.0134        | 15.0  | 3600 | 0.7055          | 0.6552    | 0.6552 | 0.6552 | 0.9257   |
| 0.0134        | 16.0  | 3840 | 0.7115          | 0.6522    | 0.6466 | 0.6494 | 0.9249   |

### Framework versions

- Transformers 4.24.0
- Pytorch 2.0.0
- Datasets 2.9.0
- Tokenizers 0.11.0