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mdeberta-pov
This model is a fine-tuned version of MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2878
- Accuracy: 0.94
- F1: 0.9400
- Precision: 0.9400
- Recall: 0.94
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: 4
- eval_batch_size: 8
- seed: 2402
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.3295 | 1.0 | 5437 | 0.2637 | 0.9165 | 0.9164 | 0.9183 | 0.9165 |
| 0.2735 | 2.0 | 10874 | 0.2912 | 0.9285 | 0.9285 | 0.9285 | 0.9285 |
| 0.1949 | 3.0 | 16311 | 0.3108 | 0.935 | 0.9350 | 0.9351 | 0.935 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3
