my_awesome_qa_model / README.md
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Training in progress epoch 2
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metadata
license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: pankaj10034/my_awesome_qa_model
    results: []

pankaj10034/my_awesome_qa_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: 3.0141
  • Train End Logits Accuracy: 0.2113
  • Train Start Logits Accuracy: 0.2113
  • Validation Loss: 3.3137
  • Validation End Logits Accuracy: 0.1825
  • Validation Start Logits Accuracy: 0.1725
  • Epoch: 2

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': 200, '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 Train End Logits Accuracy Train Start Logits Accuracy Validation Loss Validation End Logits Accuracy Validation Start Logits Accuracy Epoch
4.3640 0.0681 0.0763 3.5479 0.1350 0.1375 0
3.2351 0.1713 0.1650 3.3137 0.1825 0.1725 1
3.0141 0.2113 0.2113 3.3137 0.1825 0.1725 2

Framework versions

  • Transformers 4.30.2
  • TensorFlow 2.12.0
  • Datasets 2.13.1
  • Tokenizers 0.13.3