Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
bert-finetuned-ner – AI Model by viraxeva | AlphaNeural AI
You can deploy this model and start earning money today!
viraxeva
/
bert-finetuned-ner
like
0
transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
bert-finetuned-ner
This model is a fine-tuned version of
bert-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2481
Precision: 0.5243
Recall: 0.6409
F1: 0.5767
Accuracy: 0.9411
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: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
249
0.2331
0.4705
0.6222
0.5358
0.9351
No log
2.0
498
0.2312
0.5533
0.6101
0.5803
0.9434
0.2095
3.0
747
0.2481
0.5243
0.6409
0.5767
0.9411
Framework versions
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
