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vihealthvn – AI Model by Quym5124050 | AlphaNeural AI
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Quym5124050
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vihealthvn
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transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-multilingual-cased
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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vihealthvn
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: 0.0192
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: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
0.1615
1.0
266
0.0931
0.0674
2.0
532
0.0433
0.0474
3.0
798
0.0248
0.019
4.0
1064
0.0252
0.0297
5.0
1330
0.0192
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
