metadata
library_name: transformers
license: mit
base_model: MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Bert-Contact-NLI
results: []
Bert-Contact-NLI
This model is a fine-tuned version of MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8520
- Model Preparation Time: 0.0063
- Accuracy: 0.7222
- Precision: 0.7086
- Recall: 0.7284
- F1: 0.7134
- Ratio: 0.3611
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | Precision | Recall | F1 | Ratio |
|---|---|---|---|---|---|---|---|---|---|
| No log | 0.9895 | 47 | 0.8446 | 0.0063 | 0.6142 | 0.6097 | 0.5667 | 0.5804 | 0.5340 |
| No log | 2.0 | 95 | 0.7677 | 0.0063 | 0.6821 | 0.6774 | 0.6708 | 0.6636 | 0.3148 |
| No log | 2.9895 | 142 | 0.7705 | 0.0063 | 0.7006 | 0.6919 | 0.6740 | 0.6805 | 0.4043 |
| No log | 4.0 | 190 | 0.7969 | 0.0063 | 0.7006 | 0.6787 | 0.7153 | 0.6915 | 0.3951 |
| No log | 4.9474 | 235 | 0.8520 | 0.0063 | 0.7222 | 0.7086 | 0.7284 | 0.7134 | 0.3611 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3