balinese_bert_gelu – AI Model by pijarcandra22 | AlphaNeural AI

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pijarcandra22/
balinese_bert_gelu

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google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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balinese_bert_gelu

This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.0000

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:

learning_rate: 5e-05
train_batch_size: 60
eval_batch_size: 60
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
4.1808	1.0	2843	4.0316
3.6212	2.0	5686	3.7258
3.4379	3.0	8529	3.4925
3.2701	4.0	11372	3.3557
3.1459	5.0	14215	3.2430
2.9187	6.0	17058	3.1499
2.8706	7.0	19901	3.0879
2.7558	8.0	22744	2.9777
2.5905	9.0	25587	2.9532
2.5815	10.0	28430	3.0000

Framework versions

Transformers 4.45.2
Pytorch 2.5.1+cu124
Datasets 2.19.0
Tokenizers 0.20.3