multi-class-full-data

This model is a fine-tuned version of APaul/muril-multi-class on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.1202
• Validation Loss: 0.1385
• Train Precision: 0.7887
• Train Recall: 0.8132
• Train F1: 0.8008
• Train Accuracy: 0.9629
• Epoch: 9

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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 30000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Precision	Train Recall	Train F1	Train Accuracy	Epoch
0.1266	0.1385	0.7887	0.8132	0.8008	0.9629	0
0.1217	0.1385	0.7887	0.8132	0.8008	0.9629	1
0.1260	0.1385	0.7887	0.8132	0.8008	0.9629	2
0.1217	0.1385	0.7887	0.8132	0.8008	0.9629	3
0.1244	0.1385	0.7887	0.8132	0.8008	0.9629	4
0.1224	0.1385	0.7887	0.8132	0.8008	0.9629	5
0.1224	0.1385	0.7887	0.8132	0.8008	0.9629	6
0.1225	0.1385	0.7887	0.8132	0.8008	0.9629	7
0.1244	0.1385	0.7887	0.8132	0.8008	0.9629	8
0.1202	0.1385	0.7887	0.8132	0.8008	0.9629	9

Framework versions

• Transformers 4.44.2
• TensorFlow 2.17.0
• Datasets 3.2.0
• Tokenizers 0.19.1