---
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: 0.3318
- Precisions: 0.8562
- Recall: 0.8095
- F-measure: 0.8293
- Accuracy: 0.9476

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4465        | 1.0   | 269  | 0.3166          | 0.8058     | 0.6865 | 0.6693    | 0.9046   |
| 0.2204        | 2.0   | 538  | 0.2474          | 0.8108     | 0.7990 | 0.7979    | 0.9295   |
| 0.133         | 3.0   | 807  | 0.2529          | 0.8072     | 0.7719 | 0.7830    | 0.9357   |
| 0.087         | 4.0   | 1076 | 0.2601          | 0.8462     | 0.7886 | 0.8012    | 0.9415   |
| 0.0578        | 5.0   | 1345 | 0.2896          | 0.8286     | 0.8106 | 0.8186    | 0.9418   |
| 0.0307        | 6.0   | 1614 | 0.3017          | 0.8474     | 0.8065 | 0.8240    | 0.9433   |
| 0.0257        | 7.0   | 1883 | 0.3435          | 0.8488     | 0.8129 | 0.8270    | 0.9407   |
| 0.0159        | 8.0   | 2152 | 0.3318          | 0.8562     | 0.8095 | 0.8293    | 0.9476   |
| 0.0086        | 9.0   | 2421 | 0.3629          | 0.8433     | 0.8065 | 0.8224    | 0.9451   |
| 0.0067        | 10.0  | 2690 | 0.3700          | 0.8648     | 0.8020 | 0.8272    | 0.9451   |
| 0.0064        | 11.0  | 2959 | 0.3835          | 0.8328     | 0.8108 | 0.8203    | 0.9425   |
| 0.0041        | 12.0  | 3228 | 0.3625          | 0.8454     | 0.8094 | 0.8255    | 0.9447   |
| 0.0028        | 13.0  | 3497 | 0.3734          | 0.8450     | 0.8097 | 0.8254    | 0.9451   |
| 0.0021        | 14.0  | 3766 | 0.3706          | 0.8469     | 0.8119 | 0.8274    | 0.9462   |


### Framework versions

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