---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0410_lrate7.5b4
  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_lrate7.5b4

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: 0.4079
- Precisions: 0.7671
- Recall: 0.7305
- F-measure: 0.7455
- Accuracy: 0.8904

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.7027        | 1.0   | 942  | 0.4843          | 0.8628     | 0.6861 | 0.6969    | 0.8785   |
| 0.3645        | 2.0   | 1884 | 0.4079          | 0.7671     | 0.7305 | 0.7455    | 0.8904   |
| 0.238         | 3.0   | 2826 | 0.5338          | 0.7981     | 0.7422 | 0.7486    | 0.8957   |
| 0.1894        | 4.0   | 3768 | 0.6026          | 0.8327     | 0.7495 | 0.7668    | 0.9049   |
| 0.0825        | 5.0   | 4710 | 0.5781          | 0.7825     | 0.7859 | 0.7833    | 0.9055   |
| 0.0523        | 6.0   | 5652 | 0.6107          | 0.8084     | 0.7591 | 0.7712    | 0.9124   |
| 0.0388        | 7.0   | 6594 | 0.6455          | 0.8090     | 0.7802 | 0.7894    | 0.9107   |
| 0.0253        | 8.0   | 7536 | 0.6711          | 0.8168     | 0.7825 | 0.7937    | 0.9135   |


### Framework versions

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