DBERT_CleanDesc_v2 / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: ratish/DBERT_CleanDesc_v2
    results: []

ratish/DBERT_CleanDesc_v2

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: 0.1598
  • Validation Loss: 0.7230
  • Train Accuracy: 0.85
  • Epoch: 12

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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 6180, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Accuracy Epoch
2.2247 2.0414 0.375 0
1.6722 1.6034 0.575 1
1.2412 1.3270 0.6 2
0.9495 1.0999 0.6 3
0.7464 0.9892 0.65 4
0.6087 0.8445 0.75 5
0.4628 0.8918 0.7 6
0.3747 0.7971 0.775 7
0.3069 0.7776 0.75 8
0.2492 0.6877 0.825 9
0.2148 0.7085 0.8 10
0.1793 0.6896 0.85 11
0.1598 0.7230 0.85 12

Framework versions

  • Transformers 4.27.4
  • TensorFlow 2.12.0
  • Datasets 2.11.0
  • Tokenizers 0.13.3