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all-MiniLM-L6-v2-finetuned-iso29148-req-detector

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all-MiniLM-L6-v2-finetuned-iso29148-req-detector / README.md
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metadata
license: apache-2.0
base_model: sentence-transformers/all-MiniLM-L6-v2
tags:
  - generated_from_keras_callback
model-index:
  - name: kasrahabib/all-MiniLM-L6-v2-finetuned-isobased-req-detector_v3
    results: []

kasrahabib/all-MiniLM-L6-v2-finetuned-isobased-req-detector_v3

This model is a fine-tuned version of sentence-transformers/all-MiniLM-L6-v2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.0937
  • Validation Loss: 0.3926
  • Epoch: 29

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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3570, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Epoch
2.7669 2.5868 0
2.2742 1.8750 1
1.6937 1.4343 2
1.3318 1.1742 3
1.0835 0.9818 4
0.9073 0.8713 5
0.7707 0.7725 6
0.6586 0.6982 7
0.5697 0.6336 8
0.4915 0.6005 9
0.4294 0.5569 10
0.3730 0.5356 11
0.3214 0.4918 12
0.2801 0.4575 13
0.2496 0.4503 14
0.2151 0.4572 15
0.1918 0.4230 16
0.1767 0.4110 17
0.1604 0.4110 18
0.1471 0.4040 19
0.1380 0.4070 20
0.1282 0.3987 21
0.1242 0.4021 22
0.1185 0.3951 23
0.1108 0.3915 24
0.1058 0.3937 25
0.1037 0.3988 26
0.1000 0.3914 27
0.0989 0.3908 28
0.0937 0.3926 29

Framework versions

  • Transformers 4.40.1
  • TensorFlow 2.15.0
  • Datasets 2.19.1
  • Tokenizers 0.19.1