multiclassclassification

This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.2109
• Train Accuracy: 0.9640
• Validation Loss: 0.1246
• Validation Accuracy: 0.9791
• Epoch: 6

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': 'AdamWeightDecay', 'learning_rate': 3e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.0}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
4.3108	0.1497	3.3191	0.2857	0
2.7219	0.4440	1.7910	0.6764	1
1.5252	0.7185	0.8825	0.8578	2
0.8069	0.8690	0.4319	0.9354	3
0.4793	0.9235	0.2545	0.9609	4
0.2931	0.9526	0.1720	0.9755	5
0.2109	0.9640	0.1246	0.9791	6

Framework versions

• Transformers 4.51.3
• TensorFlow 2.18.0
• Datasets 3.6.0
• Tokenizers 0.21.1