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Albert-Bhai-Nepali – AI Model by raygx | AlphaNeural AI
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raygx
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Albert-Bhai-Nepali
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transformers
tf
albert
fill-mask
generated_from_keras_callback
mit
autotrain_compatible
endpoints_compatible
us
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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
