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xtremedistil-l6-h256-uncased-future-time-references-D1

This model is a fine-tuned version of microsoft/xtremedistil-l6-h256-uncased on the jonaskoenig/trump_administration_statement and jonaskoenig/future-time-refernces-static-filter datsets.

It achieves the following results on the evaluation set:

  • Train Loss: 0.0099
  • Train Sparse Categorical Accuracy: 0.9977
  • Validation Loss: 0.0128
  • Validation Sparse Categorical Accuracy: 0.9976
  • Epoch: 3

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
0.0276 0.9932 0.0156 0.9968 0
0.0138 0.9969 0.0125 0.9972 1
0.0117 0.9974 0.0126 0.9974 2
0.0099 0.9977 0.0128 0.9976 3

The test accuracy is: 99.77%

Framework versions

  • Transformers 4.20.1
  • TensorFlow 2.9.1
  • Datasets 2.3.2
  • Tokenizers 0.12.1
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Datasets used to train jonaskoenig/xtremedistil-l6-h256-uncased-future-time-references-D1