xtremedistil-l6-h256-uncased-question-vs-statement-classifier

This model is a fine-tuned version of microsoft/xtremedistil-l6-h256-uncased on question-vs-statement-classifier dataset, which is a clone of the kaggle Questions vs Statements Classification dataset.

It achieves the following results on the evaluation set:

• Train Loss: 0.0227
• Train Sparse Categorical Accuracy: 0.9894
• Validation Loss: 0.0294
• Validation Sparse Categorical Accuracy: 0.9868
• 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
0.0681	0.9770	0.0327	0.9839	0
0.0301	0.9856	0.0321	0.9853	1
0.0262	0.9875	0.0286	0.9864	2
0.0227	0.9894	0.0294	0.9868	3

Framework versions

• Transformers 4.20.1
• TensorFlow 2.9.1
• Datasets 2.3.2
• Tokenizers 0.12.1