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End of fine-tuning DistilBERT
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metadata
license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: pull_request_comments_model
    results: []

pull_request_comments_model

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: 0.0791
  • Train Accuracy: 0.9955
  • Validation Loss: 0.5019
  • Validation Accuracy: 0.8291
  • 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 280, '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}
  • training_precision: float32

Training results

Train Loss Train Accuracy Validation Loss Validation Accuracy Epoch
1.3102 0.4308 1.1851 0.4701 0
1.1436 0.4978 0.9891 0.6068 1
0.9590 0.6183 0.8287 0.6838 2
0.7801 0.6942 0.6916 0.7692 3
0.6074 0.7946 0.6212 0.8120 4
0.4755 0.8817 0.5471 0.8205 5
0.3503 0.9241 0.5244 0.8376 6
0.2594 0.9665 0.5171 0.8120 7
0.1711 0.9844 0.4832 0.8291 8
0.1474 0.9911 0.5000 0.8205 9
0.1082 0.9955 0.4875 0.8291 10
0.0981 0.9933 0.4928 0.8291 11
0.0791 0.9955 0.5019 0.8291 12

Framework versions

  • Transformers 4.26.1
  • TensorFlow 2.9.0
  • Datasets 2.10.1
  • Tokenizers 0.13.2