---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert_seed33_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_seed33_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: 0.3569
- Precisions: 0.8341
- Recall: 0.8159
- F-measure: 0.8240
- Accuracy: 0.9424

## 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: 33
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4471        | 1.0   | 236  | 0.2653          | 0.7696     | 0.7076 | 0.7131    | 0.9195   |
| 0.2264        | 2.0   | 472  | 0.2367          | 0.8184     | 0.7497 | 0.7777    | 0.9279   |
| 0.1443        | 3.0   | 708  | 0.2710          | 0.8069     | 0.7735 | 0.7817    | 0.9315   |
| 0.0869        | 4.0   | 944  | 0.2697          | 0.8391     | 0.7998 | 0.8150    | 0.9364   |
| 0.0531        | 5.0   | 1180 | 0.2877          | 0.8622     | 0.7952 | 0.8178    | 0.9393   |
| 0.0373        | 6.0   | 1416 | 0.3171          | 0.8338     | 0.8120 | 0.8204    | 0.9422   |
| 0.0238        | 7.0   | 1652 | 0.3312          | 0.8247     | 0.7921 | 0.8047    | 0.9390   |
| 0.0159        | 8.0   | 1888 | 0.3569          | 0.8341     | 0.8159 | 0.8240    | 0.9424   |
| 0.0122        | 9.0   | 2124 | 0.3832          | 0.8398     | 0.8127 | 0.8238    | 0.9422   |
| 0.0058        | 10.0  | 2360 | 0.4160          | 0.8288     | 0.7975 | 0.8098    | 0.9400   |
| 0.0059        | 11.0  | 2596 | 0.4153          | 0.8321     | 0.8012 | 0.8124    | 0.9405   |
| 0.0045        | 12.0  | 2832 | 0.4399          | 0.8130     | 0.7909 | 0.7994    | 0.9369   |
| 0.0024        | 13.0  | 3068 | 0.4357          | 0.8358     | 0.8026 | 0.8163    | 0.9409   |
| 0.0035        | 14.0  | 3304 | 0.4391          | 0.8374     | 0.8036 | 0.8175    | 0.9414   |


### Framework versions

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