importance_model

This model is a fine-tuned version of hfl/chinese-roberta-wwm-ext on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.4867
• Train Sparse Categorical Accuracy: 0.8389
• Validation Loss: 0.6060
• Validation Sparse Categorical Accuracy: 0.8016
• 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
0.7037	0.7614	0.6077	0.7964	0
0.5683	0.8120	0.5615	0.8106	1
0.4867	0.8389	0.6060	0.8016	2

Framework versions

• Transformers 4.16.0
• TensorFlow 2.7.0
• Datasets 1.18.1
• Tokenizers 0.11.0