eternis's picture
Model save
d4ce2be verified
metadata
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: []

eternis_router_encoder_sft_11Sep

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: 0.4944
  • 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