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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: 0.0336
  • Validation Loss: 1.1880
  • Train F1: 0.0391
  • Epoch: 17

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
0.0336 1.1880 0.0391 17

Framework versions

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