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: 0.5215
Accuracy: 0.8984
F1: 0.8984

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: 64
eval_batch_size: 256
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 512
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 0.06
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	40	0.6523	0.8683	0.8678
8.3995	2.0	80	0.5242	0.8957	0.8957
4.6207	3.0	120	0.5215	0.8984	0.8984

Framework versions

Transformers 5.5.4
Pytorch 2.11.0+cu130
Datasets 4.8.4
Tokenizers 0.22.2

sytnaxerror/robbert-L-dbrd

robbert-L-dbrd

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sytnaxerror/
robbert-L-dbrd