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distilbert-base-uncased-finetuned-sms-spam – AI Model by aimanabdulmanan | AlphaNeural AI
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distilbert-base-uncased-finetuned-sms-spam
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transformers
tensorboard
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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distilbert-base-uncased-finetuned-sms-spam
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: 0.0491
Accuracy: 0.9892
F1: 0.9891
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: 64
eval_batch_size: 64
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
F1
0.158
1.0
70
0.0515
0.9901
0.9900
0.0356
2.0
140
0.0491
0.9892
0.9891
Framework versions
Transformers 4.52.4
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.21.4
