This model is a fine-tuned version of DTAI-KULeuven/robbert-2023-dutch-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.8711

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: 6e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss
2.3132	1.0	69	2.1302
2.1372	2.0	138	2.0750
2.0204	3.0	207	1.9985
1.9231	4.0	276	1.9298
1.8671	5.0	345	1.9031
1.764	6.0	414	1.9241
1.7491	7.0	483	1.9061
1.7057	8.0	552	1.9247
1.6751	9.0	621	1.8435
1.5922	10.0	690	1.8714
1.5859	11.0	759	1.8203
1.5551	12.0	828	1.8823

Framework versions

Transformers 4.31.0
Pytorch 1.11.0+cu113
Datasets 2.14.4
Tokenizers 0.13.3

btamm12/robbert-2023-dutch-large-ft-lcn

robbert-2023-dutch-large-ft-lcn

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

btamm12/
robbert-2023-dutch-large-ft-lcn