---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0410_lrate10b8
  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_lrate10b8

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: 0.6067
- Precisions: 0.8082
- Recall: 0.7813
- F-measure: 0.7929
- Accuracy: 0.9106

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6356        | 1.0   | 471  | 0.4207          | 0.8357     | 0.6959 | 0.6907    | 0.8767   |
| 0.3636        | 2.0   | 942  | 0.3759          | 0.7587     | 0.7486 | 0.7497    | 0.8938   |
| 0.2131        | 3.0   | 1413 | 0.4114          | 0.8027     | 0.7381 | 0.7548    | 0.8966   |
| 0.1356        | 4.0   | 1884 | 0.4721          | 0.8141     | 0.7498 | 0.7682    | 0.9015   |
| 0.0768        | 5.0   | 2355 | 0.5470          | 0.7628     | 0.7637 | 0.7575    | 0.8969   |
| 0.0459        | 6.0   | 2826 | 0.5884          | 0.7864     | 0.7783 | 0.7807    | 0.9109   |
| 0.0267        | 7.0   | 3297 | 0.6067          | 0.8082     | 0.7813 | 0.7929    | 0.9106   |
| 0.0183        | 8.0   | 3768 | 0.6205          | 0.7964     | 0.7684 | 0.7786    | 0.9090   |


### Framework versions

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