---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: robbert-v2-dutch-base-finetuned-sentiment
  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. -->

# robbert-v2-dutch-base-finetuned-sentiment

This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2055
- Accuracy: 0.3673
- F1: 0.3712

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0698        | 1.0   | 86   | 1.0615          | 0.4898   | 0.3314 |
| 1.0312        | 2.0   | 172  | 1.0980          | 0.4052   | 0.3792 |
| 0.9602        | 3.0   | 258  | 1.2286          | 0.4169   | 0.3583 |
| 0.8644        | 4.0   | 344  | 1.2476          | 0.4315   | 0.3893 |
| 0.7201        | 5.0   | 430  | 1.4700          | 0.4227   | 0.3993 |
| 0.5759        | 6.0   | 516  | 1.6862          | 0.3848   | 0.3821 |
| 0.477         | 7.0   | 602  | 1.9556          | 0.3469   | 0.3529 |
| 0.3852        | 8.0   | 688  | 2.0945          | 0.3586   | 0.3637 |
| 0.3377        | 9.0   | 774  | 2.1969          | 0.3440   | 0.3502 |
| 0.2965        | 10.0  | 860  | 2.2055          | 0.3673   | 0.3712 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1