mbert-wili-model – AI Model by ShawnSean | AlphaNeural AI

You can deploy this model and start earning money today!

ShawnSean/
mbert-wili-model

like

0

text-classification

generated_from_trainer

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

Views

No views yet

mbert-wili-model

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: 0.1530
Accuracy: 0.9710

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: 2e-05
train_batch_size: 64
eval_batch_size: 128
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5164	1.0	1469	0.3606	0.9373
0.2156	2.0	2938	0.1900	0.9573
0.1358	3.0	4407	0.1638	0.9620
0.0937	4.0	5876	0.1490	0.9673
0.0604	5.0	7345	0.1541	0.9663
0.0324	6.0	8814	0.1453	0.9695
0.0215	7.0	10283	0.1475	0.9703
0.0155	8.0	11752	0.1489	0.9711
0.0087	9.0	13221	0.1508	0.9715
0.0072	10.0	14690	0.1519	0.9715

Framework versions

Transformers 4.52.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1