---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0210_lrate5b8
  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_lrate5b8

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: 0.3595
- Precisions: 0.8049
- Recall: 0.7503
- F-measure: 0.7661
- Accuracy: 0.8987

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| No log        | 1.0   | 471  | 0.4152          | 0.8420     | 0.6873 | 0.6895    | 0.8762   |
| 0.6244        | 2.0   | 942  | 0.3595          | 0.8049     | 0.7503 | 0.7661    | 0.8987   |
| 0.3086        | 3.0   | 1413 | 0.3926          | 0.8113     | 0.7757 | 0.7838    | 0.9110   |
| 0.1676        | 4.0   | 1884 | 0.4826          | 0.7805     | 0.7526 | 0.7628    | 0.9025   |
| 0.1044        | 5.0   | 2355 | 0.5530          | 0.8001     | 0.7627 | 0.7769    | 0.9028   |
| 0.0571        | 6.0   | 2826 | 0.5910          | 0.7945     | 0.7661 | 0.7765    | 0.9103   |
| 0.0321        | 7.0   | 3297 | 0.6168          | 0.8251     | 0.7733 | 0.7899    | 0.9124   |
| 0.0234        | 8.0   | 3768 | 0.6218          | 0.8108     | 0.7748 | 0.7881    | 0.9116   |


### Framework versions

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