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---
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
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