---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert_seed35_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_seed35_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: 0.3736
- Precisions: 0.8703
- Recall: 0.8320
- F-measure: 0.8460
- Accuracy: 0.9455

## 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: 35
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4597        | 1.0   | 236  | 0.2601          | 0.8795     | 0.7027 | 0.7178    | 0.9224   |
| 0.2359        | 2.0   | 472  | 0.2642          | 0.7554     | 0.7436 | 0.7448    | 0.9209   |
| 0.1425        | 3.0   | 708  | 0.2765          | 0.8100     | 0.7809 | 0.7872    | 0.9318   |
| 0.0893        | 4.0   | 944  | 0.2727          | 0.8404     | 0.7708 | 0.7885    | 0.9340   |
| 0.0597        | 5.0   | 1180 | 0.3136          | 0.8572     | 0.7712 | 0.7963    | 0.9361   |
| 0.0446        | 6.0   | 1416 | 0.3246          | 0.8474     | 0.7824 | 0.7947    | 0.9409   |
| 0.029         | 7.0   | 1652 | 0.3266          | 0.8266     | 0.7944 | 0.7985    | 0.9361   |
| 0.0181        | 8.0   | 1888 | 0.3377          | 0.8564     | 0.8139 | 0.8257    | 0.9422   |
| 0.0152        | 9.0   | 2124 | 0.3578          | 0.8240     | 0.8439 | 0.8297    | 0.9426   |
| 0.0121        | 10.0  | 2360 | 0.3270          | 0.8659     | 0.8292 | 0.8444    | 0.9475   |
| 0.0094        | 11.0  | 2596 | 0.3510          | 0.8742     | 0.8274 | 0.8455    | 0.9467   |
| 0.0057        | 12.0  | 2832 | 0.3674          | 0.8435     | 0.8350 | 0.8379    | 0.9441   |
| 0.0042        | 13.0  | 3068 | 0.3746          | 0.8708     | 0.8313 | 0.8458    | 0.9458   |
| 0.0027        | 14.0  | 3304 | 0.3736          | 0.8703     | 0.8320 | 0.8460    | 0.9455   |


### Framework versions

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