---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: eternis_router_encoder_sft_4Sep
  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_4Sep

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: 0.1710
- Mse: 0.1710
- Model Accuracy: 0.3285

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch 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: 0.06
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Mse    | Model Accuracy |
|:-------------:|:------:|:----:|:---------------:|:------:|:--------------:|
| 0.4021        | 0.3429 | 300  | 0.1875          | 0.1875 | 0.153          |
| 0.3702        | 0.6857 | 600  | 0.1809          | 0.1809 | 0.1757         |
| 0.36          | 1.0286 | 900  | 0.1762          | 0.1762 | 0.3068         |
| 0.3686        | 1.3714 | 1200 | 0.1788          | 0.1788 | 0.2333         |
| 0.3337        | 1.7143 | 1500 | 0.1733          | 0.1733 | 0.3192         |
| 0.3293        | 2.0571 | 1800 | 0.1709          | 0.1709 | 0.3297         |
| 0.3245        | 2.4    | 2100 | 0.1706          | 0.1706 | 0.3035         |
| 0.3158        | 2.7429 | 2400 | 0.1710          | 0.1710 | 0.3285         |


### Framework versions

- Transformers 4.56.0
- Pytorch 2.7.0
- Datasets 4.0.0
- Tokenizers 0.22.0