---
license: apache-2.0
base_model: google/mobilebert-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scam-alert-mobile-bert
  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. -->

# scam-alert-mobile-bert

This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7097
- Accuracy: 0.9880
- F1: 0.9880

## 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: 8
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.1577 | 100  | 0.4729          | 0.9223   | 0.9145 |
| No log        | 0.3155 | 200  | 2.1621          | 0.9801   | 0.9803 |
| No log        | 0.4732 | 300  | 0.8327          | 0.9900   | 0.9900 |
| No log        | 0.6309 | 400  | 3.3648          | 0.9900   | 0.9900 |
| No log        | 0.7886 | 500  | 0.8376          | 0.9861   | 0.9861 |
| No log        | 0.9464 | 600  | 0.7630          | 0.9861   | 0.9861 |
| No log        | 1.1041 | 700  | 0.6559          | 0.9861   | 0.9861 |
| No log        | 1.2618 | 800  | 2.2440          | 0.9880   | 0.9880 |
| No log        | 1.4196 | 900  | 2.4358          | 0.9900   | 0.9900 |
| No log        | 1.5773 | 1000 | 1.9655          | 0.9861   | 0.9859 |
| No log        | 1.7350 | 1100 | 1.8927          | 0.9880   | 0.9880 |
| No log        | 1.8927 | 1200 | 1.3919          | 0.9880   | 0.9880 |
| No log        | 2.0505 | 1300 | 0.9143          | 0.9861   | 0.9860 |
| No log        | 2.2082 | 1400 | 0.1891          | 0.9861   | 0.9859 |
| No log        | 2.3659 | 1500 | 0.0815          | 0.9861   | 0.9861 |
| No log        | 2.5237 | 1600 | 0.0853          | 0.9880   | 0.9880 |
| No log        | 2.6814 | 1700 | 0.2719          | 0.9861   | 0.9860 |
| No log        | 2.8391 | 1800 | 0.2175          | 0.9900   | 0.9900 |
| No log        | 2.9968 | 1900 | 0.5407          | 0.9880   | 0.9880 |
| No log        | 3.1546 | 2000 | 0.8695          | 0.9880   | 0.9880 |
| No log        | 3.3123 | 2100 | 0.1031          | 0.9880   | 0.9880 |
| No log        | 3.4700 | 2200 | 1.1922          | 0.9900   | 0.9900 |
| No log        | 3.6278 | 2300 | 0.4830          | 0.9880   | 0.9880 |
| No log        | 3.7855 | 2400 | 1.4562          | 0.9880   | 0.9880 |
| No log        | 3.9432 | 2500 | 1.8929          | 0.9900   | 0.9900 |
| 2789.4062     | 4.1009 | 2600 | 0.6560          | 0.9880   | 0.9880 |
| 2789.4062     | 4.2587 | 2700 | 0.1473          | 0.9841   | 0.9842 |
| 2789.4062     | 4.4164 | 2800 | 0.3488          | 0.9880   | 0.9880 |
| 2789.4062     | 4.5741 | 2900 | 0.2347          | 0.9880   | 0.9880 |
| 2789.4062     | 4.7319 | 3000 | 0.7488          | 0.9900   | 0.9900 |
| 2789.4062     | 4.8896 | 3100 | 0.5055          | 0.9880   | 0.9880 |
| 2789.4062     | 5.0473 | 3200 | 0.8339          | 0.9900   | 0.9900 |
| 2789.4062     | 5.2050 | 3300 | 0.5382          | 0.9880   | 0.9880 |
| 2789.4062     | 5.3628 | 3400 | 0.6095          | 0.9880   | 0.9880 |
| 2789.4062     | 5.5205 | 3500 | 0.7142          | 0.9880   | 0.9880 |
| 2789.4062     | 5.6782 | 3600 | 0.6855          | 0.9880   | 0.9880 |
| 2789.4062     | 5.8360 | 3700 | 0.7152          | 0.9880   | 0.9880 |
| 2789.4062     | 5.9937 | 3800 | 0.7097          | 0.9880   | 0.9880 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1