---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: eternis_router_encoder_sft_11Sep
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# eternis_router_encoder_sft_11Sep

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4944
- Model Accuracy: 0.7861

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Model Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------------:|
| 0.535         | 1.0602  | 300  | 0.5205          | 0.7730         |
| 0.5295        | 2.1204  | 600  | 0.5053          | 0.7764         |
| 0.5166        | 3.1805  | 900  | 0.5038          | 0.7811         |
| 0.5138        | 4.2407  | 1200 | 0.5009          | 0.7807         |
| 0.5196        | 5.3009  | 1500 | 0.5048          | 0.7761         |
| 0.4977        | 6.3611  | 1800 | 0.5034          | 0.7795         |
| 0.4924        | 7.4212  | 2100 | 0.4970          | 0.7803         |
| 0.4915        | 8.4814  | 2400 | 0.5084          | 0.7749         |
| 0.4903        | 9.5416  | 2700 | 0.4960          | 0.7830         |
| 0.4942        | 10.6018 | 3000 | 0.4945          | 0.7873         |
| 0.4926        | 11.6619 | 3300 | 0.4955          | 0.7807         |
| 0.5057        | 12.7221 | 3600 | 0.4929          | 0.7826         |
| 0.4916        | 13.7823 | 3900 | 0.4939          | 0.7838         |
| 0.4953        | 14.8425 | 4200 | 0.4948          | 0.7807         |
| 0.4919        | 15.9027 | 4500 | 0.4947          | 0.7834         |
| 0.5043        | 16.9628 | 4800 | 0.4944          | 0.7854         |
| 0.4768        | 18.0212 | 5100 | 0.4944          | 0.7857         |
| 0.4879        | 19.0814 | 5400 | 0.4944          | 0.7861         |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.0