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ditilbert-spamEmail – AI Model by tony4194 | AlphaNeural AI
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tony4194
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ditilbert-spamEmail
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transformers
pytorch
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
Files and Versions
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API
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ditilbert-spamEmail
This model is a fine-tuned version of
distilbert-base-uncased
on an
enron_spam dataset
. It achieves the following results on the evaluation set:
Loss: 0.0462
Accuracy: 0.9925
Model description
By calling the API, label 0 means ham message while 1 means spam message.
Intended uses & limitations
This model is used for spam email detection powered by distilbert and sequence classification.
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
0.0307
1.0
1983
0.0561
0.989
0.007
2.0
3966
0.0462
0.9925
Framework versions
Transformers 4.34.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.1
