akaashp15's picture
Training in progress epoch 2
e69aba1
|
raw
history blame
2.04 kB
metadata
license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: akaashp15/distilbert-base-uncased-finetuned-ner
    results: []

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