akaashp15/distilbert-base-uncased-finetuned-ner

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

• Train Loss: 0.0344
• Validation Loss: 0.0597
• Train Precision: 0.9253
• Train Recall: 0.9356
• Train F1: 0.9304
• Train Accuracy: 0.9836
• 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': 'Adam', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2631, '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}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Precision	Train Recall	Train F1	Train Accuracy	Epoch
0.1990	0.0712	0.8974	0.9226	0.9098	0.9790	0
0.0544	0.0612	0.9148	0.9318	0.9232	0.9822	1
0.0344	0.0597	0.9253	0.9356	0.9304	0.9836	2

Framework versions

• Transformers 4.30.2
• TensorFlow 2.13.0-rc2
• Datasets 2.13.1
• Tokenizers 0.13.3