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metadata
license: mit
tags:
  - generated_from_keras_callback
model-index:
  - name: huynhdoo/distilcamembert-base-finetuned-jva-missions-report
    results: []

huynhdoo/distilcamembert-base-finetuned-jva-missions-report

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

  • Train Loss: 0.0299
  • Validation Loss: 1.0017
  • Train F1: 0.0279
  • Epoch: 16

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': 3000, '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 Validation Loss Train F1 Epoch
0.5225 0.4756 0.3575 0
0.4079 0.4294 0.2961 1
0.3439 0.5053 0.2961 2
0.2765 0.5106 0.2346 3
0.2044 0.5352 0.1788 4
0.1774 0.6706 0.1341 5
0.1690 0.8693 0.1676 6
0.1143 0.7711 0.0726 7
0.0930 0.9906 0.0950 8
0.1091 0.9093 0.1117 9
0.0576 0.8518 0.0894 10
0.0500 1.2538 0.0950 11
0.0541 0.7193 0.0838 12
0.0461 0.9906 0.0503 13
0.0359 0.9036 0.0447 14
0.0320 1.1648 0.0391 15
0.0299 1.0017 0.0279 16

Framework versions

  • Transformers 4.26.0
  • TensorFlow 2.9.2
  • Datasets 2.9.0
  • Tokenizers 0.13.2