---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: irony_nl_Netherlands
  results: []
---


# irony_nl_Netherlands

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on part of the MultiPICo dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0030
- Accuracy: 0.5738
- Precision: 0.2735
- Recall: 0.6275
- F1: 0.3810

## Model description

The model is trained considering the annotation of annotators from the Netherlands only, on instances in Dutch. The Dutch annotations from these annotators are aggregated using majority voting and then used to train the model.

## Training and evaluation data

The model has been trained on the annotation from annotators from the Netherlands from the MultiPICo dataset (instances in Dutch). The data has been randomly split into a train and a validation set.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0045        | 1.0   | 46   | 0.0043          | 0.7008   | 0.1562    | 0.0980 | 0.1205 |
| 0.0041        | 2.0   | 92   | 0.0042          | 0.7336   | 0.2083    | 0.0980 | 0.1333 |
| 0.004         | 3.0   | 138  | 0.0041          | 0.6393   | 0.2239    | 0.2941 | 0.2542 |
| 0.004         | 4.0   | 184  | 0.0039          | 0.4754   | 0.2484    | 0.7451 | 0.3725 |
| 0.0037        | 5.0   | 230  | 0.0037          | 0.5697   | 0.2589    | 0.5686 | 0.3558 |
| 0.0034        | 6.0   | 276  | 0.0036          | 0.4713   | 0.2532    | 0.7843 | 0.3828 |
| 0.0036        | 7.0   | 322  | 0.0036          | 0.5656   | 0.2477    | 0.5294 | 0.3375 |
| 0.0037        | 8.0   | 368  | 0.0036          | 0.5      | 0.2482    | 0.6863 | 0.3646 |
| 0.0031        | 9.0   | 414  | 0.0035          | 0.5287   | 0.2612    | 0.6863 | 0.3784 |
| 0.0034        | 10.0  | 460  | 0.0036          | 0.5369   | 0.25      | 0.6078 | 0.3543 |
| 0.0029        | 11.0  | 506  | 0.0035          | 0.5410   | 0.256     | 0.6275 | 0.3636 |
| 0.003         | 12.0  | 552  | 0.0032          | 0.5492   | 0.2677    | 0.6667 | 0.3820 |
| 0.0028        | 13.0  | 598  | 0.0030          | 0.5164   | 0.2752    | 0.8039 | 0.41   |
| 0.0026        | 14.0  | 644  | 0.0028          | 0.5574   | 0.2857    | 0.7451 | 0.4130 |
| 0.0024        | 15.0  | 690  | 0.0030          | 0.5820   | 0.2893    | 0.6863 | 0.4070 |
| 0.0023        | 16.0  | 736  | 0.0030          | 0.5738   | 0.2735    | 0.6275 | 0.3810 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1