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---
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
|