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Nicknotname/
wnutNer

transformers

distilbert

token-classification

generated_from_keras_callback

distilbert/distilbert-base-uncased

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Nicknotname/wnutNer

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.1137
Validation Loss: 0.2552
Train Precision: 0.5898
Train Recall: 0.4163
Train F1: 0.4881
Train Accuracy: 0.9467
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
0.3393	0.3197	0.3455	0.0455	0.0803	0.9248	0
0.1550	0.2591	0.5387	0.3744	0.4418	0.9433	1
0.1137	0.2552	0.5898	0.4163	0.4881	0.9467	2

Framework versions

Transformers 4.41.2
TensorFlow 2.15.0
Datasets 2.19.2
Tokenizers 0.19.1