---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0210_lrate5b4
  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. -->

# robbert0210_lrate5b4

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: 0.3947
- Precisions: 0.7931
- Recall: 0.7419
- F-measure: 0.7620
- Accuracy: 0.8995

## 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: 5e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.71          | 1.0   | 942  | 0.4675          | 0.8146     | 0.6895 | 0.6795    | 0.8713   |
| 0.3587        | 2.0   | 1884 | 0.3947          | 0.7931     | 0.7419 | 0.7620    | 0.8995   |
| 0.2221        | 3.0   | 2826 | 0.5259          | 0.7885     | 0.7682 | 0.7650    | 0.9021   |
| 0.1455        | 4.0   | 3768 | 0.5330          | 0.8071     | 0.7500 | 0.7698    | 0.9051   |
| 0.0775        | 5.0   | 4710 | 0.5904          | 0.7773     | 0.7806 | 0.7768    | 0.9035   |
| 0.0465        | 6.0   | 5652 | 0.6671          | 0.8375     | 0.7689 | 0.7890    | 0.9038   |
| 0.0329        | 7.0   | 6594 | 0.6634          | 0.8002     | 0.7764 | 0.7864    | 0.9073   |
| 0.0245        | 8.0   | 7536 | 0.6707          | 0.8325     | 0.7928 | 0.8087    | 0.9118   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3