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cakiki/distilbert-base-uncased-finetuned-tweet-sentiment

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: 0.1025
  • Train Sparse Categorical Accuracy: 0.9511
  • Validation Loss: 0.1455
  • Validation Sparse Categorical Accuracy: 0.9365
  • 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', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Train Sparse Categorical Accuracy Validation Loss Validation Sparse Categorical Accuracy Epoch
0.5409 0.8158 0.2115 0.9265 0
0.1442 0.9373 0.1411 0.9380 1
0.1025 0.9511 0.1455 0.9365 2

Framework versions

  • Transformers 4.18.0
  • TensorFlow 2.9.0-rc0
  • Datasets 2.1.0
  • Tokenizers 0.12.1
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