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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: answerdotai/ModernBERT-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: ModernRadBERT-mlm |
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results: [] |
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--- |
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# ModernRadBERT-mlm |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6936 |
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https://www.johnpaulett.com/2025/modernbert-radiology-fine-tuning-masked-langage-model/ |
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**WARNING: For demonstration purposes only** |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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**Not intended for real-world use**, was an example of MLM fine-tuning on a small radiology dataset. |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.8693 | 1.0 | 248 | 1.5996 | |
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| 1.6968 | 2.0 | 496 | 1.7973 | |
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| 1.7187 | 3.0 | 744 | 1.7232 | |
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| 1.6518 | 4.0 | 992 | 1.7343 | |
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| 1.5003 | 5.0 | 1240 | 1.7727 | |
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| 1.3346 | 6.0 | 1488 | 1.7357 | |
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| 1.4029 | 7.0 | 1736 | 1.7164 | |
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| 1.2762 | 8.0 | 1984 | 1.7123 | |
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| 1.2441 | 9.0 | 2232 | 1.6978 | |
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| 1.2016 | 10.0 | 2480 | 1.7374 | |
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| 1.1887 | 11.0 | 2728 | 1.7076 | |
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| 1.0205 | 12.0 | 2976 | 1.6736 | |
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| 1.0771 | 13.0 | 3224 | 1.7209 | |
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| 1.0607 | 14.0 | 3472 | 1.6753 | |
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| 0.909 | 15.0 | 3720 | 1.6172 | |
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| 0.9255 | 16.0 | 3968 | 1.7418 | |
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| 0.8676 | 17.0 | 4216 | 1.6914 | |
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| 0.8533 | 18.0 | 4464 | 1.7310 | |
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| 0.845 | 19.0 | 4712 | 1.7893 | |
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| 0.869 | 20.0 | 4960 | 1.6936 | |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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