---
library_name: transformers
license: mit
base_model: DTAI-KULeuven/robbert-2023-dutch-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: robbert-2023-dutch-large-topic_classification
  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. -->

# robbert-2023-dutch-large-topic_classification

This model is a fine-tuned version of [DTAI-KULeuven/robbert-2023-dutch-large](https://huggingface.co/DTAI-KULeuven/robbert-2023-dutch-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7479
- Precision: 0.9198
- Recall: 0.9008
- F1: 0.9082
- Accuracy: 0.9118

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 88   | 0.7486          | 0.8471    | 0.8101 | 0.8223 | 0.8333   |
| No log        | 2.0   | 176  | 0.7488          | 0.8557    | 0.7525 | 0.7800 | 0.8137   |
| No log        | 3.0   | 264  | 0.9650          | 0.8507    | 0.8430 | 0.8347 | 0.8284   |
| No log        | 4.0   | 352  | 0.7878          | 0.8982    | 0.8472 | 0.8650 | 0.8775   |
| No log        | 5.0   | 440  | 0.8113          | 0.9254    | 0.8876 | 0.9020 | 0.9020   |
| 0.5488        | 6.0   | 528  | 0.8695          | 0.9070    | 0.8858 | 0.8936 | 0.8971   |
| 0.5488        | 7.0   | 616  | 0.7924          | 0.9174    | 0.8886 | 0.8983 | 0.9020   |
| 0.5488        | 8.0   | 704  | 0.6974          | 0.9198    | 0.9008 | 0.9082 | 0.9118   |
| 0.5488        | 9.0   | 792  | 0.7410          | 0.9292    | 0.9065 | 0.9148 | 0.9167   |
| 0.5488        | 10.0  | 880  | 0.7479          | 0.9198    | 0.9008 | 0.9082 | 0.9118   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1