This model is a fine-tuned version of pdelobelle/robbert-v2-dutch-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3848
Precisions: 0.8521
Recall: 0.8198
F-measure: 0.8327
Accuracy: 0.9441

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: 7.5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 37
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 14

Training results

Training Loss	Epoch	Step	Validation Loss	Precisions	Recall	F-measure	Accuracy
0.4569	1.0	236	0.2571	0.7110	0.7130	0.7092	0.9217
0.222	2.0	472	0.2286	0.7904	0.7574	0.7685	0.9313
0.1311	3.0	708	0.2412	0.8047	0.7810	0.7875	0.9359
0.0813	4.0	944	0.2755	0.8019	0.7775	0.7886	0.9354
0.0552	5.0	1180	0.3120	0.8499	0.7793	0.8032	0.9409
0.0323	6.0	1416	0.3536	0.8350	0.7955	0.8099	0.9402
0.0212	7.0	1652	0.3789	0.8448	0.7817	0.8092	0.9405
0.0154	8.0	1888	0.3835	0.8419	0.7780	0.7971	0.9385
0.0119	9.0	2124	0.3906	0.8583	0.7812	0.8058	0.9388
0.0081	10.0	2360	0.3910	0.8477	0.7874	0.8062	0.9424
0.0052	11.0	2596	0.3839	0.8642	0.8087	0.8298	0.9431
0.0046	12.0	2832	0.3848	0.8521	0.8198	0.8327	0.9441
0.0018	13.0	3068	0.4017	0.8450	0.8125	0.8240	0.9438
0.0014	14.0	3304	0.4060	0.8571	0.8088	0.8265	0.9441

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1

Tommert25/robbert_seed37_1311

robbert_seed37_1311

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Tommert25/
robbert_seed37_1311