---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0410_lrate10b16
  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. -->

# robbert0410_lrate10b16

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: 0.4783
- Precisions: 0.8324
- Recall: 0.8123
- F-measure: 0.8208
- Accuracy: 0.9164

## 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: 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6379        | 1.0   | 236  | 0.4156          | 0.8657     | 0.6790 | 0.6955    | 0.8798   |
| 0.3257        | 2.0   | 472  | 0.3378          | 0.7529     | 0.7397 | 0.7336    | 0.8932   |
| 0.1977        | 3.0   | 708  | 0.3737          | 0.7960     | 0.7383 | 0.7451    | 0.9003   |
| 0.1197        | 4.0   | 944  | 0.4060          | 0.8446     | 0.7503 | 0.7696    | 0.9025   |
| 0.0659        | 5.0   | 1180 | 0.4428          | 0.7851     | 0.7731 | 0.7779    | 0.9063   |
| 0.0447        | 6.0   | 1416 | 0.4972          | 0.8285     | 0.7991 | 0.8124    | 0.9127   |
| 0.0256        | 7.0   | 1652 | 0.4783          | 0.8324     | 0.8123 | 0.8208    | 0.9164   |
| 0.0173        | 8.0   | 1888 | 0.4918          | 0.8251     | 0.8082 | 0.8159    | 0.9169   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0