---
license: apache-2.0
base_model: Matthijsvanhof/bert-base-dutch-cased-finetuned-mBERT
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-dutch-cased-finetuned-mBERT-finetuned-ner
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-dutch-cased-finetuned-mBERT-finetuned-ner

This model is a fine-tuned version of [Matthijsvanhof/bert-base-dutch-cased-finetuned-mBERT](https://huggingface.co/Matthijsvanhof/bert-base-dutch-cased-finetuned-mBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0127
- Precision: 0.9780
- Recall: 0.9889
- F1: 0.9834
- Accuracy: 0.9969

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 25   | 0.0395          | 0.8673    | 0.9444 | 0.9043 | 0.9876   |
| No log        | 2.0   | 50   | 0.0159          | 0.9780    | 0.9889 | 0.9834 | 0.9953   |
| No log        | 3.0   | 75   | 0.0127          | 0.9780    | 0.9889 | 0.9834 | 0.9969   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2+cpu
- Datasets 2.19.2
- Tokenizers 0.19.1