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bert-ambiguous-query-detector – AI Model by hoaan | AlphaNeural AI
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bert-ambiguous-query-detector
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transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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bert-ambiguous-query-detector
This model is a fine-tuned version of
google-bert/bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6599
Accuracy: 0.6173
F1: 0.6171
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: 1e-05
train_batch_size: 16
eval_batch_size: 16
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: 6
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.6658
1.0
568
0.6319
0.6408
0.6374
0.6053
2.0
1136
0.6172
0.6646
0.6646
0.5454
3.0
1704
0.6590
0.6505
0.6494
0.4681
4.0
2272
0.7095
0.6400
0.6400
Framework versions
Transformers 4.57.6
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.2
