Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
bert-finetuned-ner – AI Model by TripleTa | AlphaNeural AI
You can deploy this model and start earning money today!
TripleTa
/
bert-finetuned-ner
like
0
transformers
tf
bert
token-classification
generated_from_keras_callback
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
TripleTa/bert-finetuned-ner
This model is a fine-tuned version of
bert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.0218
Validation Loss: 0.0539
Epoch: 2
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:
optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2634, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': np.float32(0.9), 'beta_2': np.float32(0.999), 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: mixed_float16
Training results
Train Loss
Validation Loss
Epoch
0.0471
0.0600
0
0.0277
0.0539
1
0.0218
0.0539
2
Framework versions
Transformers 4.52.4
TensorFlow 2.18.0
Datasets 3.6.0
Tokenizers 0.21.1
