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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-large |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: ModernBERT-large-llm-router |
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results: [] |
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datasets: |
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- DevQuasar/llm_router_dataset-synth |
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pipeline_tag: text-classification |
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--- |
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# ModernBERT-large-llm-router |
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This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on [DevQuasar/llm_router_dataset-synth](https://huggingface.co/datasets/DevQuasar/llm_router_dataset-synth). |
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It achieves the following results on the test set: |
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- Loss: 0.0536 |
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- F1: 0.9933 |
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## Model description |
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See original [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) model card for additional information. This model is intended to classify queries for LLM routing. More advanced queries get labeled 1 for large_llm and simpler queries get 0 for small_llm. |
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## Training procedure |
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Annotated training procedure available [in this notebook.](https://colab.research.google.com/drive/1G7oHp_8R4fmOSpjwaNB_T2NUJsmMh4Kw?usp=sharing) Methodology and code credits to [Phillip Schmid](https://huggingface.co/philschmid) from his [Fine-tune classifier with ModernBERT in 2025 |
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](https://www.philschmid.de/fine-tune-modern-bert-in-2025) blog post. |
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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: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use adamw_torch_fused 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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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.0303 | 1.0 | 479 | 0.0317 | 0.9881 | |
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| 0.014 | 2.0 | 958 | 0.0374 | 0.9927 | |
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| 0.0044 | 3.0 | 1437 | 0.0502 | 0.9921 | |
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| 0.0004 | 4.0 | 1916 | 0.0554 | 0.9927 | |
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| 0.0003 | 5.0 | 2395 | 0.0536 | 0.9933 | |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.21.0 |
