metadata
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: []
eternis_router_encoder_sft_4Sep
This model is a fine-tuned version of 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