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twitter_bank_scam_classifier – AI Model by Colabng | AlphaNeural AI
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Colabng
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twitter_bank_scam_classifier
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peft
tensorboard
safetensors
bert
text-classification
adapter
lora
transformers
google-bert/bert-base-uncased
apache-2.0
us
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twitter_bank_scam_classifier
This model is a fine-tuned version of
google-bert/bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6349
Accuracy: 0.73
Auc: 0.75
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: 0.001
train_batch_size: 8
eval_batch_size: 8
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Auc
0.7136
1.0
11
0.6374
0.68
0.7
0.6544
2.0
22
0.6349
0.73
0.75
Framework versions
PEFT 0.16.0
Transformers 4.53.3
Pytorch 2.7.1+cu126
Datasets 4.0.0
Tokenizers 0.21.2
