metadata
library_name: transformers
license: mit
base_model: MoritzLaurer/mDeBERTa-v3-base-mnli-xnli
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: target-abroad-fr
results: []
target-abroad-fr
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: 0.5710
- Accuracy: 0.9154
- Precision: 0.7473
- Recall: 0.8
- F1: 0.7727
- Roc Auc: 0.9454
- Pr Auc: 0.8535
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc | Pr Auc |
|---|---|---|---|---|---|---|---|---|---|
| 0.3696 | 1.0 | 168 | 0.2849 | 0.8901 | 0.6460 | 0.8588 | 0.7374 | 0.9560 | 0.8138 |
| 0.2846 | 2.0 | 336 | 0.3283 | 0.8985 | 0.6609 | 0.8941 | 0.76 | 0.9541 | 0.8112 |
| 0.2046 | 3.0 | 504 | 0.5015 | 0.9239 | 0.7816 | 0.8 | 0.7907 | 0.9483 | 0.8495 |
| 0.1169 | 4.0 | 672 | 0.5710 | 0.9154 | 0.7473 | 0.8 | 0.7727 | 0.9454 | 0.8535 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.9.0+cu126
- Datasets 4.5.0
- Tokenizers 0.22.2