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sms-spam-distilbert – AI Model by hafzafarooq | AlphaNeural AI
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sms-spam-distilbert
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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sms-spam-distilbert
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: 0.0562
Accuracy: 0.9892
Precision: 0.9907
Recall: 0.9298
F1: 0.9593
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: 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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.0505
1.0
244
0.0320
0.9916
0.9655
0.9739
0.9697
0.0186
2.0
488
0.0271
0.9952
1.0
0.9652
0.9823
0.0085
3.0
732
0.0286
0.9952
1.0
0.9652
0.9823
Framework versions
Transformers 5.12.1
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
