veriga/tf_disilbert

veriga

This model is a fine-tuned version of veriga/distilbert-base-uncased-finetuned-cola on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 1.9335
• Train Sparse Categorical Accuracy: 0.4537
• Validation Loss: 1.9743
• Validation Sparse Categorical Accuracy: 0.4488
• 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
1.9359	0.4543	1.9947	0.4505	0
1.9330	0.4547	1.9796	0.4514	1
1.9335	0.4537	1.9743	0.4488	2

Framework versions

• Transformers 4.36.2
• TensorFlow 2.8.2
• Datasets 2.2.2
• Tokenizers 0.15.0