---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0510_lrate7.5b32
  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. -->

# robbert0510_lrate7.5b32

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: 0.5259
- Precisions: 0.8050
- Recall: 0.7984
- F-measure: 0.8013
- Accuracy: 0.9128

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6483        | 1.0   | 118  | 0.3862          | 0.8737     | 0.6655 | 0.6815    | 0.8772   |
| 0.3233        | 2.0   | 236  | 0.3337          | 0.7936     | 0.7423 | 0.7497    | 0.8995   |
| 0.1934        | 3.0   | 354  | 0.3600          | 0.7488     | 0.7661 | 0.7482    | 0.8980   |
| 0.1207        | 4.0   | 472  | 0.3525          | 0.8202     | 0.7535 | 0.7731    | 0.9056   |
| 0.0775        | 5.0   | 590  | 0.4264          | 0.7906     | 0.7756 | 0.7811    | 0.8998   |
| 0.05          | 6.0   | 708  | 0.4335          | 0.8100     | 0.7965 | 0.7999    | 0.9087   |
| 0.0335        | 7.0   | 826  | 0.4759          | 0.8380     | 0.7810 | 0.7987    | 0.9107   |
| 0.0249        | 8.0   | 944  | 0.5115          | 0.8254     | 0.7788 | 0.7976    | 0.9100   |
| 0.014         | 9.0   | 1062 | 0.5206          | 0.8249     | 0.7883 | 0.7973    | 0.9107   |
| 0.0082        | 10.0  | 1180 | 0.5259          | 0.8050     | 0.7984 | 0.8013    | 0.9128   |
| 0.0061        | 11.0  | 1298 | 0.5238          | 0.8068     | 0.7953 | 0.8005    | 0.9118   |
| 0.0056        | 12.0  | 1416 | 0.5385          | 0.8059     | 0.7939 | 0.7995    | 0.9114   |


### Framework versions

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