my_awesome_wnut_model – AI Model by mahabharahta | AlphaNeural AI

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mahabharahta/
my_awesome_wnut_model

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token-classification

generated_from_keras_callback

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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mahabharahta/my_awesome_wnut_model

This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.0944
Validation Loss: 0.2261
Train Precision: 0.6429
Train Recall: 0.4737
Train F1: 0.5455
Train Accuracy: 0.9509
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': 636, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32

Training results

Train Loss	Validation Loss	Train Precision	Train Recall	Train F1	Train Accuracy	Epoch
0.2774	0.2932	0.5372	0.2416	0.3333	0.9359	0
0.1424	0.2377	0.6149	0.4258	0.5032	0.9481	1
0.0944	0.2261	0.6429	0.4737	0.5455	0.9509	2

Framework versions

Transformers 4.44.2
TensorFlow 2.17.0
Datasets 3.0.1
Tokenizers 0.19.1