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

# peft-modernbert-base

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0410
- Accuracy: 0.9887
- Matthews Correlation: 0.9850
- F1: 0.9760
- Precision: 0.9730
- Recall: 0.9792

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Matthews Correlation | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------------:|:------:|:---------:|:------:|
| 0.5348        | 0.1977 | 1400 | 0.0968          | 0.9722   | 0.9631               | 0.9568 | 0.9528    | 0.9609 |
| 0.2975        | 0.3954 | 2800 | 0.0728          | 0.9808   | 0.9745               | 0.9637 | 0.9559    | 0.9725 |
| 0.2385        | 0.5931 | 4200 | 0.0518          | 0.9865   | 0.9821               | 0.9731 | 0.9685    | 0.9780 |
| 0.2500        | 0.7908 | 5600 | 0.0443          | 0.9882   | 0.9843               | 0.9752 | 0.9709    | 0.9803 |
| 0.1968        | 0.9885 | 7000 | 0.0410          | 0.9887   | 0.9850               | 0.9760 | 0.9730    | 0.9792 |


### Framework versions

- PEFT 0.18.1
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2