---
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: 0.8136
- Accuracy: 0.8189
- F1: 0.8189
- Recall: 0.7604

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
| 0.5247        | 1.0   | 32   | 0.4726          | 0.8110   | 0.8092 | 0.7083 |
| 0.2684        | 2.0   | 64   | 0.5090          | 0.7874   | 0.7897 | 0.7917 |
| 0.1319        | 3.0   | 96   | 0.7653          | 0.8031   | 0.8027 | 0.7292 |
| 0.035         | 4.0   | 128  | 0.8136          | 0.8189   | 0.8189 | 0.7604 |


### Framework versions

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