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spam-classifier – AI Model by chingoduc | AlphaNeural AI
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spam-classifier
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transformers
pytorch
tensorboard
distilbert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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spam-classifier
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0539
Accuracy: 0.9914
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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
262
0.0424
0.9899
0.053
2.0
524
0.0473
0.9914
0.053
3.0
786
0.0497
0.9907
0.0062
4.0
1048
0.0522
0.9914
0.0062
5.0
1310
0.0539
0.9914
Framework versions
Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3
