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ViSoBERT_prompt_classifier – AI Model by Minh64 | AlphaNeural AI
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Minh64
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ViSoBERT_prompt_classifier
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transformers
tensorboard
safetensors
xlm-roberta
text-classification
generated_from_trainer
uitnlp/visobert
finetune
autotrain_compatible
endpoints_compatible
us
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ViSoBERT_prompt_classifier
This model is a fine-tuned version of
uitnlp/visobert
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0121
Accuracy: 0.9974
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
0.0374
0.9907
0.0213
2.0
504
0.0119
0.9974
0.0213
3.0
756
0.0121
0.9974
Framework versions
Transformers 4.51.3
Pytorch 2.5.1+cu121
Datasets 3.6.0
Tokenizers 0.21.0
