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