---
library_name: peft
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- base_model:adapter:answerdotai/ModernBERT-base
- lora
- transformers
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: modernbert-synth-vishing
  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. -->

# modernbert-synth-vishing

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0835
- Accuracy: 0.9702
- F1: 0.9768
- Precision: 0.9800
- Recall: 0.9736

## 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: 32
- 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: 100
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5618        | 1.0   | 99   | 0.5515          | 0.7031   | 0.8109 | 0.6882    | 0.9868 |
| 0.2574        | 2.0   | 198  | 0.2440          | 0.8920   | 0.9142 | 0.9375    | 0.8921 |
| 0.1227        | 3.0   | 297  | 0.1477          | 0.9389   | 0.9534 | 0.9382    | 0.9692 |
| 0.0810        | 4.0   | 396  | 0.1099          | 0.9659   | 0.9735 | 0.9757    | 0.9714 |
| 0.0488        | 5.0   | 495  | 0.1082          | 0.9659   | 0.9739 | 0.9634    | 0.9846 |
| 0.0419        | 6.0   | 594  | 0.0882          | 0.9744   | 0.9802 | 0.9781    | 0.9824 |
| 0.0285        | 7.0   | 693  | 0.0835          | 0.9702   | 0.9768 | 0.9800    | 0.9736 |


### Framework versions

- PEFT 0.19.1
- Transformers 5.10.2
- Pytorch 2.11.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2