---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
- spam
model-index:
- name: ZachBeesley/Spam-Detector
  results: []
datasets:
- sms_spam
widget:
- text: >-
    WINNER!! As a valued network customer you have been selected to receivea
    £900 prize reward! To claim call 09061701461. Claim code KL341. Valid 12
    hours only.
  example_title: Example 1
language:
- en
metrics:
- accuracy
---


<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# ZachBeesley/Spam-Detector

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0093
- Epoch: 2

## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1740, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Epoch |
|:----------:|:-----:|
| 0.0644     | 0     |
| 0.0209     | 1     |
| 0.0093     | 2     |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.1
- Tokenizers 0.13.3