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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_keras_callback
model-index:
  - name: Dung111/distilbert-base-uncased-finetuned-squad
    results: []

Dung111/distilbert-base-uncased-finetuned-squad

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: 2.8629
  • Train End Logits Accuracy: 0.2996
  • Train Start Logits Accuracy: 0.2862
  • Validation Loss: 2.8396
  • Validation End Logits Accuracy: 0.3094
  • Validation Start Logits Accuracy: 0.3183
  • Epoch: 1

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': 252, '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 Train End Logits Accuracy Train Start Logits Accuracy Validation Loss Validation End Logits Accuracy Validation Start Logits Accuracy Epoch
4.3395 0.0799 0.0714 3.5811 0.1680 0.1473 0
2.8629 0.2996 0.2862 2.8396 0.3094 0.3183 1

Framework versions

  • Transformers 4.44.0
  • TensorFlow 2.17.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1