---
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: cyber_distilbert
  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_distilbert

This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4491
- Accuracy: 0.7971
- F1: 0.7871
- Precision: 0.7824
- Recall: 0.8099

## 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: 1e-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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4835        | 1.0   | 144  | 0.4918          | 0.7543   | 0.7486 | 0.7571    | 0.7859 |
| 0.4014        | 2.0   | 288  | 0.4116          | 0.7992   | 0.7831 | 0.7774    | 0.7927 |
| 0.3788        | 3.0   | 432  | 0.4453          | 0.7872   | 0.7777 | 0.7746    | 0.8027 |
| 0.3943        | 4.0   | 576  | 0.4264          | 0.8018   | 0.7903 | 0.7843    | 0.8090 |
| 0.3518        | 5.0   | 720  | 0.4491          | 0.7971   | 0.7871 | 0.7824    | 0.8099 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1