xtremedistil-l6-h256-uncased-future-time-references-D2 – AI Model by jonaskoenig | AlphaNeural AI

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jonaskoenig/
xtremedistil-l6-h256-uncased-future-time-references-D2

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text-classification

generated_from_keras_callback

jonaskoenig/trump_administration_statement

jonaskoenig/future-time-refernces-static-filter-D2

autotrain_compatible

endpoints_compatible

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xtremedistil-l6-h256-uncased-future-time-references-D2

This model is a fine-tuned version of microsoft/xtremedistil-l6-h256-uncased on jonaskoenig/future-time-refernces-static-filter-D2 and jonaskoenig/trump_administration_statement. It achieves the following results on the evaluation set:

Train Loss: 0.0055
Train Sparse Categorical Accuracy: 0.9984
Validation Loss: 0.0074
Validation Sparse Categorical Accuracy: 0.9984
Epoch: 4

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
0.0388	0.9891	0.0154	0.9957	0
0.0133	0.9962	0.0088	0.9975	1
0.0087	0.9974	0.0081	0.9978	2
0.0068	0.9980	0.0074	0.9982	3
0.0055	0.9984	0.0074	0.9984	4

The test accuracy is: 99.81%

Framework versions

Transformers 4.20.1
TensorFlow 2.9.1
Datasets 2.3.2
Tokenizers 0.12.1