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PhoBERT_prompt_classifier – AI Model by Minh64 | AlphaNeural AI
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Minh64
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PhoBERT_prompt_classifier
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transformers
tensorboard
safetensors
roberta
text-classification
generated_from_trainer
vinai/phobert-base-v2
finetune
agpl-3.0
autotrain_compatible
endpoints_compatible
us
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PhoBERT_prompt_classifier
This model is a fine-tuned version of
vinai/phobert-base-v2
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0110
Accuracy: 0.9977
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 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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
252
0.0312
0.9919
0.0425
2.0
504
0.0110
0.9977
0.0425
3.0
756
0.0110
0.9977
Framework versions
Transformers 4.51.3
Pytorch 2.5.1+cu121
Datasets 3.6.0
Tokenizers 0.21.0
