results / README.md
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rationalenterprise/fine_tuned_spam_model
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---
library_name: transformers
base_model: mrm8488/bert-tiny-finetuned-sms-spam-detection
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results
This model is a fine-tuned version of [mrm8488/bert-tiny-finetuned-sms-spam-detection](https://huggingface.co/mrm8488/bert-tiny-finetuned-sms-spam-detection) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0884
- Accuracy: 0.5480
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1383 | 1.0 | 42 | 1.1377 | 0.5367 |
| 1.0594 | 2.0 | 84 | 1.0975 | 0.5424 |
| 1.0472 | 3.0 | 126 | 1.0884 | 0.5480 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cpu
- Datasets 3.3.2
- Tokenizers 0.21.1