irony_nl_Netherlands

Multilingual-Perspectivist-NLU/irony_nl_Netherlands

irony_nl_Netherlands is a text classification model from Multilingual-Perspectivist-NLU. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

This model is a fine-tuned version of 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…

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: roberta
Access: Public
Created: Nov 6, 2023
Updated: Nov 6, 2023
SHA: 99f2ad67

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Model card

From the Hugging Face model README

irony_nl_Netherlands

This model is a fine-tuned version of 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

Task: Text Classification
Library: transformers
Type: roberta
License: mit
Created: Nov 6, 2023
Updated: Nov 6, 2023