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fraud_text_detection – AI Model by austinb | AlphaNeural AI
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austinb
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fraud_text_detection
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transformers
pytorch
onnx
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
quantized
apache-2.0
autotrain_compatible
endpoints_compatible
us
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fraud_text_detection
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1112
Accuracy: 0.9798
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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
334
0.0931
0.9815
0.0671
2.0
668
0.1112
0.9798
Framework versions
Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.5
Tokenizers 0.14.1
