Tommert25/RobBERTBestModelOct11

robbert0410_lrate7.5b16

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: 0.5355
• Precisions: 0.8523
• Recall: 0.8173
• F-measure: 0.8307
• Accuracy: 0.9209

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: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss	Precisions	Recall	F-measure	Accuracy
0.6127	1.0	236	0.3656	0.8687	0.6888	0.7011	0.8817
0.3078	2.0	472	0.3390	0.8253	0.7452	0.7612	0.8947
0.1742	3.0	708	0.3899	0.7602	0.7560	0.7469	0.8957
0.1242	4.0	944	0.4402	0.8560	0.7678	0.7861	0.9055
0.0749	5.0	1180	0.4206	0.8163	0.8139	0.8127	0.9121
0.0533	6.0	1416	0.4824	0.8257	0.7936	0.8060	0.9124
0.0366	7.0	1652	0.4927	0.8506	0.7956	0.8158	0.9176
0.0273	8.0	1888	0.5638	0.8631	0.7855	0.8093	0.9202
0.0206	9.0	2124	0.5507	0.8322	0.7957	0.8096	0.9141
0.0154	10.0	2360	0.5355	0.8523	0.8173	0.8307	0.9209
0.0105	11.0	2596	0.5812	0.8301	0.7961	0.8088	0.9162
0.0086	12.0	2832	0.6084	0.8357	0.8065	0.8192	0.9130
0.0046	13.0	3068	0.6035	0.8310	0.7948	0.8104	0.9137
0.0036	14.0	3304	0.6034	0.8223	0.7980	0.8074	0.9134
0.0043	15.0	3540	0.6146	0.8198	0.7869	0.7999	0.9120
0.0018	16.0	3776	0.6070	0.8244	0.7894	0.8029	0.9134

Framework versions

• Transformers 4.34.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.14.0