ModernBERT-large-llm-router
This model is a fine-tuned version of the answerdotai/ModernBERT-large model using the DevQuasar/llm_router_dataset-synth dataset.
The fine-tuned model achieves the following results on the test set:
- Loss: 0.0555
- F1: 0.9933
This model was trained using a RTX 4090
Model description
See original answerdotai/ModernBERT-base model card for additional information. This model is intended to classify queries for LLM routing. where advanced/complicated queries are labeled as 1 (large_llm) and simpler queries are labeled as 0 (small_llm).
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- gradient_accumulation_steps: 2
- bf16: True
- seed: 42
- optimizer: Use adamw_torch_fused
- lr_scheduler_type: linear
- num_epochs: 5
Training Code
GITHUB URL TO BE ADDED
Training results
Epoch | Validation Loss | F1 |
---|---|---|
1.0 | 0.0296 | 0.9907 |
2.0 | 0.0327 | 0.9911 |
3.0 | 0.0474 | 0.9933 |
4.0 | 0.0563 | 0.9933 |
5.0 | 0.0554 | 0.9933 |
- Downloads last month
- 24
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Model tree for anthonyivn/ModernBERT-Base-llm-router
Base model
answerdotai/ModernBERT-base