---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: PaymentNonPayment-ModernBERT
  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. -->

# PaymentNonPayment-ModernBERT

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: 0.0157
- Accuracy: 0.9985
- F1: 0.9985
- Precision: 0.9985
- Recall: 0.9985
- Roc Auc: 0.9984

## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Roc Auc |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|
| 16.0312       | 0.1996 | 79   | 0.1616          | 0.9823   | 0.9823 | 0.9829    | 0.9823 | 0.9803  |
| 0.0001        | 0.3992 | 158  | 0.1080          | 0.9882   | 0.9882 | 0.9884    | 0.9882 | 0.9890  |
| 0.0001        | 0.5989 | 237  | 0.0169          | 0.9985   | 0.9985 | 0.9985    | 0.9985 | 0.9984  |
| 0.0003        | 0.7985 | 316  | 0.0138          | 0.9985   | 0.9985 | 0.9985    | 0.9985 | 0.9984  |
| 0.0001        | 0.9981 | 395  | 0.0157          | 0.9985   | 0.9985 | 0.9985    | 0.9985 | 0.9984  |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0