bert-base-dutch-cased-finetuned-mBERT

This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0898
• Precision: 0.7255
• Recall: 0.7255
• F1: 0.7255
• Accuracy: 0.9758

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1603	1.0	533	0.0928	0.6896	0.6962	0.6929	0.9742
0.0832	2.0	1066	0.0898	0.7255	0.7255	0.7255	0.9758

Framework versions

• Transformers 4.12.5
• Pytorch 1.10.0+cu111
• Tokenizers 0.10.3