metadata
library_name: transformers
license: mit
base_model: MoritzLaurer/mDeBERTa-v3-base-mnli-xnli
tags:
- generated_from_trainer
model-index:
- name: outputs_target_abroad_de_final
results: []
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