Beta
Explore
Marketplace
Neural Labs
Playground
Wallet
Docs
BERT-Router-base – AI Model by AmirMohseni | AlphaNeural AI
You can deploy this model and start earning money today!
AmirMohseni
/
BERT-Router-base
like
0
transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
BERT-Router-v1
This model is a fine-tuned version of
google-bert/bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1199
Accuracy: 0.955
Auc: 0.992
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: 256
eval_batch_size: 256
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 512
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: 10
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Auc
0.134
2.1778
50
0.1322
0.949
0.991
0.1212
4.3556
100
0.1267
0.951
0.991
0.1199
6.5333
150
0.1223
0.953
0.992
0.1193
8.7111
200
0.1199
0.955
0.992
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu121
Datasets 3.3.0
Tokenizers 0.21.0
