---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BERT-Router-large-v2
  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. -->

# BERT-Router-large-v2

This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3815
- Accuracy: 0.838
- Auc: 0.951

## 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: 1e-06
- train_batch_size: 1024
- eval_batch_size: 1024
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Auc   | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:-----:|:--------:|:---------------:|
| 0.3719        | 1.0   | 12   | 0.949 | 0.835    | 0.3895          |
| 0.3741        | 2.0   | 24   | 0.949 | 0.835    | 0.3886          |
| 0.3673        | 3.0   | 36   | 0.949 | 0.836    | 0.3879          |
| 0.3692        | 4.0   | 48   | 0.949 | 0.836    | 0.3873          |
| 0.3724        | 5.0   | 60   | 0.3866| 0.836    | 0.95            |
| 0.3683        | 6.0   | 72   | 0.3859| 0.836    | 0.95            |
| 0.3678        | 7.0   | 84   | 0.3853| 0.836    | 0.95            |
| 0.3671        | 8.0   | 96   | 0.3847| 0.837    | 0.95            |
| 0.3614        | 9.0   | 108  | 0.3842| 0.837    | 0.95            |
| 0.3658        | 10.0  | 120  | 0.3838| 0.837    | 0.95            |
| 0.3681        | 11.0  | 132  | 0.3834| 0.837    | 0.95            |
| 0.3642        | 12.0  | 144  | 0.3831| 0.837    | 0.95            |
| 0.3659        | 13.0  | 156  | 0.3827| 0.837    | 0.95            |
| 0.3693        | 14.0  | 168  | 0.3823| 0.838    | 0.95            |
| 0.3637        | 15.0  | 180  | 0.3820| 0.838    | 0.951           |
| 0.3596        | 16.0  | 192  | 0.3819| 0.838    | 0.951           |
| 0.3732        | 17.0  | 204  | 0.3817| 0.838    | 0.951           |
| 0.3685        | 18.0  | 216  | 0.3816| 0.838    | 0.951           |
| 0.3613        | 19.0  | 228  | 0.3815| 0.838    | 0.951           |
| 0.3656        | 20.0  | 240  | 0.3815| 0.838    | 0.951           |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3