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---
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