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fine_tuned_spam_model_2

Text Classification
Transformers
Safetensors
bert
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fine_tuned_spam_model_2 / README.md
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metadata
library_name: transformers
base_model: huawei-noah/TinyBERT_General_4L_312D
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: fine_tuned_spam_model_2
    results: []

fine_tuned_spam_model_2

This model is a fine-tuned version of huawei-noah/TinyBERT_General_4L_312D on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0182
  • Accuracy: 1.0

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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Use 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: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0743 1.0 125 0.0591 1.0
0.0262 2.0 250 0.0230 1.0
0.0201 3.0 375 0.0182 1.0

Framework versions

  • Transformers 4.49.0
  • Pytorch 2.6.0+cpu
  • Datasets 3.3.2
  • Tokenizers 0.21.1