---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert_seed37_1311
  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_seed37_1311

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: 0.3848
- Precisions: 0.8521
- Recall: 0.8198
- F-measure: 0.8327
- Accuracy: 0.9441

## 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: 37
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4569        | 1.0   | 236  | 0.2571          | 0.7110     | 0.7130 | 0.7092    | 0.9217   |
| 0.222         | 2.0   | 472  | 0.2286          | 0.7904     | 0.7574 | 0.7685    | 0.9313   |
| 0.1311        | 3.0   | 708  | 0.2412          | 0.8047     | 0.7810 | 0.7875    | 0.9359   |
| 0.0813        | 4.0   | 944  | 0.2755          | 0.8019     | 0.7775 | 0.7886    | 0.9354   |
| 0.0552        | 5.0   | 1180 | 0.3120          | 0.8499     | 0.7793 | 0.8032    | 0.9409   |
| 0.0323        | 6.0   | 1416 | 0.3536          | 0.8350     | 0.7955 | 0.8099    | 0.9402   |
| 0.0212        | 7.0   | 1652 | 0.3789          | 0.8448     | 0.7817 | 0.8092    | 0.9405   |
| 0.0154        | 8.0   | 1888 | 0.3835          | 0.8419     | 0.7780 | 0.7971    | 0.9385   |
| 0.0119        | 9.0   | 2124 | 0.3906          | 0.8583     | 0.7812 | 0.8058    | 0.9388   |
| 0.0081        | 10.0  | 2360 | 0.3910          | 0.8477     | 0.7874 | 0.8062    | 0.9424   |
| 0.0052        | 11.0  | 2596 | 0.3839          | 0.8642     | 0.8087 | 0.8298    | 0.9431   |
| 0.0046        | 12.0  | 2832 | 0.3848          | 0.8521     | 0.8198 | 0.8327    | 0.9441   |
| 0.0018        | 13.0  | 3068 | 0.4017          | 0.8450     | 0.8125 | 0.8240    | 0.9438   |
| 0.0014        | 14.0  | 3304 | 0.4060          | 0.8571     | 0.8088 | 0.8265    | 0.9441   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1