outputs_target_abroad_de_final

This model is a fine-tuned version of MoritzLaurer/mDeBERTa-v3-base-mnli-xnli on the None dataset. It achieves the following results on the evaluation set:

• Loss: nan
• Accuracy Mc: 0.5
• Precision Macro: 0.25
• Recall Macro: 0.5
• F1 Macro: 0.3333
• Precision Weighted: 0.25
• Recall Weighted: 0.5
• F1 Weighted: 0.3333
• Accuracy Bin: 0.5
• Precision Bin: 0.0
• Recall Bin: 0.0
• F1 Bin: 0.0
• Auc Bin: nan

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: 16
• eval_batch_size: 16
• seed: 42
• 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: linear
• lr_scheduler_warmup_steps: 0.06
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy Mc	Precision Macro	Recall Macro	F1 Macro	Precision Weighted	Recall Weighted	F1 Weighted	Accuracy Bin	Precision Bin	Recall Bin	F1 Bin	Auc Bin
0.0	1.0	490	nan	0.5	0.25	0.5	0.3333	0.25	0.5	0.3333	0.5	0.0	0.0	0.0	nan
0.0	2.0	980	nan	0.5	0.25	0.5	0.3333	0.25	0.5	0.3333	0.5	0.0	0.0	0.0	nan
0.0	3.0	1470	nan	0.5	0.25	0.5	0.3333	0.25	0.5	0.3333	0.5	0.0	0.0	0.0	nan

Framework versions

• Transformers 5.0.0
• Pytorch 2.9.0+cu126
• Datasets 4.5.0
• Tokenizers 0.22.2