---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0410_lrate10b4
  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_lrate10b4

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: 0.6818
- Precisions: 0.7943
- Recall: 0.7761
- F-measure: 0.7846
- Accuracy: 0.9080

## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6936        | 1.0   | 942  | 0.5273          | 0.8577     | 0.7062 | 0.7069    | 0.8731   |
| 0.4407        | 2.0   | 1884 | 0.4780          | 0.7487     | 0.7080 | 0.7142    | 0.8898   |
| 0.3023        | 3.0   | 2826 | 0.5526          | 0.7743     | 0.7209 | 0.7150    | 0.8904   |
| 0.2057        | 4.0   | 3768 | 0.5627          | 0.7815     | 0.7405 | 0.7559    | 0.8998   |
| 0.1333        | 5.0   | 4710 | 0.5509          | 0.7959     | 0.7521 | 0.7680    | 0.9010   |
| 0.0896        | 6.0   | 5652 | 0.6215          | 0.7844     | 0.7583 | 0.7699    | 0.9053   |
| 0.0538        | 7.0   | 6594 | 0.6694          | 0.7851     | 0.7723 | 0.7766    | 0.9025   |
| 0.0316        | 8.0   | 7536 | 0.6818          | 0.7943     | 0.7761 | 0.7846    | 0.9080   |


### Framework versions

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