---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
model-index:
- name: requirements_ambiguity_v2
  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. -->

# requirements_ambiguity_v2

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: 0.7485
- Accuracy: 0.8458
- F1: 0.8442
- Recall: 0.7474

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
| 0.5268        | 1.0   | 36   | 0.5424          | 0.8063   | 0.8057 | 0.7263 |
| 0.318         | 2.0   | 72   | 0.4688          | 0.8182   | 0.8182 | 0.7579 |
| 0.1244        | 3.0   | 108  | 0.6019          | 0.8379   | 0.8366 | 0.7474 |
| 0.0308        | 4.0   | 144  | 0.7485          | 0.8458   | 0.8442 | 0.7474 |


### Framework versions

- Transformers 4.24.0
- Pytorch 2.0.0
- Datasets 2.9.0
- Tokenizers 0.11.0