---
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
- f1
model-index:
- name: NL_BERT_michelin_finetuned
  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. -->

# NL_BERT_michelin_finetuned

This model is a fine-tuned version of [GroNLP/bert-base-dutch-cased](https://huggingface.co/GroNLP/bert-base-dutch-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0637
- Accuracy: 0.9836
- Recall: 0.5486
- Precision: 0.7914
- F1: 0.6480
- Mse: 0.0164

## 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: 32
- eval_batch_size: 128
- 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 | Accuracy | Recall | Precision | F1     | Mse    |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
| 0.1043        | 1.0   | 3647  | 0.0961          | 0.9792   | 0.3566 | 0.7606    | 0.4856 | 0.0208 |
| 0.0799        | 2.0   | 7294  | 0.0797          | 0.9803   | 0.4364 | 0.7415    | 0.5495 | 0.0197 |
| 0.0589        | 3.0   | 10941 | 0.0637          | 0.9836   | 0.5486 | 0.7914    | 0.6480 | 0.0164 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1