---
license: mit
base_model: MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: cyber_deberta
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# cyber_deberta

This model is a fine-tuned version of [MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4223
- Accuracy: 0.8320
- F1: 0.8216
- Precision: 0.8144
- Recall: 0.8401

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4368        | 1.0   | 144  | 0.4103          | 0.8117   | 0.8002 | 0.7936    | 0.8180 |
| 0.336         | 2.0   | 288  | 0.3805          | 0.8315   | 0.8186 | 0.8117    | 0.8305 |
| 0.3028        | 3.0   | 432  | 0.4287          | 0.8268   | 0.8186 | 0.8132    | 0.8442 |
| 0.248         | 4.0   | 576  | 0.4223          | 0.8320   | 0.8216 | 0.8144    | 0.8401 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1