robbert-large-with-toxi-text

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: 0.7601
• Accuracy: 0.8271
• F1: 0.8098

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: 256
• eval_batch_size: 512
• seed: 42
• gradient_accumulation_steps: 2
• 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
0.6922	1.0	5627	0.7867	0.8216	0.7971
0.6675	2.0	11254	0.7577	0.8269	0.8108
0.6406	3.0	16881	0.7601	0.8271	0.8098

Framework versions

• Transformers 5.3.0
• Pytorch 2.12.0.dev20260403+cu132
• Datasets 4.8.2
• Tokenizers 0.22.2