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Spam-messages-Classificationr – AI Model by Eafzxc | AlphaNeural AI
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Spam-messages-Classificationr
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transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-chinese
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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Spam-messages-Classificationr
This model is a fine-tuned version of
bert-base-chinese
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0006
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: 2e-05
train_batch_size: 16
eval_batch_size: 4
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
100
0.0022
1.0
No log
2.0
200
0.0030
0.9975
No log
3.0
300
0.0006
1.0
Framework versions
Transformers 5.0.0
Pytorch 2.6.0+cu124
Datasets 4.5.0
Tokenizers 0.22.2