---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: ModernRadBERT-mlm
  results: []
---



# ModernRadBERT-mlm

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the [`unsloth/Radiology_mini`](https://huggingface.co/datasets/unsloth/Radiology_mini) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6936

https://www.johnpaulett.com/2025/modernbert-radiology-fine-tuning-masked-langage-model/

**WARNING: For demonstration purposes only**

## Model description

More information needed

## Intended uses & limitations

**Not intended for real-world use**, was an example of MLM fine-tuning on a small radiology dataset. 

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8693        | 1.0   | 248  | 1.5996          |
| 1.6968        | 2.0   | 496  | 1.7973          |
| 1.7187        | 3.0   | 744  | 1.7232          |
| 1.6518        | 4.0   | 992  | 1.7343          |
| 1.5003        | 5.0   | 1240 | 1.7727          |
| 1.3346        | 6.0   | 1488 | 1.7357          |
| 1.4029        | 7.0   | 1736 | 1.7164          |
| 1.2762        | 8.0   | 1984 | 1.7123          |
| 1.2441        | 9.0   | 2232 | 1.6978          |
| 1.2016        | 10.0  | 2480 | 1.7374          |
| 1.1887        | 11.0  | 2728 | 1.7076          |
| 1.0205        | 12.0  | 2976 | 1.6736          |
| 1.0771        | 13.0  | 3224 | 1.7209          |
| 1.0607        | 14.0  | 3472 | 1.6753          |
| 0.909         | 15.0  | 3720 | 1.6172          |
| 0.9255        | 16.0  | 3968 | 1.7418          |
| 0.8676        | 17.0  | 4216 | 1.6914          |
| 0.8533        | 18.0  | 4464 | 1.7310          |
| 0.845         | 19.0  | 4712 | 1.7893          |
| 0.869         | 20.0  | 4960 | 1.6936          |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0