---
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: 0.2675
- Accuracy: 0.968
- Recall: 0.1562
- Precision: 0.5
- F1: 0.2381
- Mse: 0.032

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1     | Mse   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----:|
| 0.1078        | 1.0   | 125  | 0.2461          | 0.969    | 0.0312 | 1.0       | 0.0606 | 0.031 |
| 0.0258        | 2.0   | 250  | 0.2353          | 0.969    | 0.2188 | 0.5385    | 0.3111 | 0.031 |
| 0.0011        | 3.0   | 375  | 0.2675          | 0.968    | 0.1562 | 0.5       | 0.2381 | 0.032 |


### Framework versions

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