Edit model card

Rocketknight1/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: 0.2026
  • Validation Loss: 0.0726
  • Train Precision: 0.8945
  • Train Recall: 0.9220
  • Train F1: 0.9081
  • Train Accuracy: 0.9793
  • Epoch: 0

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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2631, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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
0.2026 0.0726 0.8945 0.9220 0.9081 0.9793 0

Framework versions

  • Transformers 4.21.0.dev0
  • TensorFlow 2.9.1
  • Datasets 2.3.3.dev0
  • Tokenizers 0.11.0
Downloads last month
23
Hosted inference API
Token Classification
Examples
Examples
This model can be loaded on the Inference API on-demand.