---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: ModernBERT-large-llm-router
  results: []
datasets:
- DevQuasar/llm_router_dataset-synth
pipeline_tag: text-classification
---

# ModernBERT-large-llm-router

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).

It achieves the following results on the test set:
- Loss: 0.0536
- F1: 0.9933

## Model description

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.

## Training procedure

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
](https://www.philschmid.de/fine-tune-modern-bert-in-2025) blog post.

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0303        | 1.0   | 479  | 0.0317          | 0.9881 |
| 0.014         | 2.0   | 958  | 0.0374          | 0.9927 |
| 0.0044        | 3.0   | 1437 | 0.0502          | 0.9921 |
| 0.0004        | 4.0   | 1916 | 0.0554          | 0.9927 |
| 0.0003        | 5.0   | 2395 | 0.0536          | 0.9933 |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0