raygx/Albert-Bhai-Nepali

This model is a fine-tuned version of Shushant/nepaliBERT on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 7.8042
• Validation Loss: 7.7339
• 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': 5e-06, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.001}
• training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
9.9774	9.7237	0
9.5636	9.3764	1
9.2524	9.0893	2
8.9711	8.8166	3
8.7139	8.5716	4
8.4774	8.3449	5
8.2628	8.1481	6
8.0779	7.9643	7
7.9268	7.8574	8
7.8042	7.7339	9

Framework versions

• Transformers 4.29.2
• TensorFlow 2.12.0
• Datasets 2.12.0
• Tokenizers 0.13.3