---
library_name: transformers
tags:
- spam
- text-classificatiom
---

Spam Classifier model - fine-tuned ModernBERT with max_length = 1024 in training. 
Trained for 5 epochs - best model selected from traning step ~600/epoch 2-3.

Model was trained with the 'sharecreative/spam_classifier_february_2025' dataset.
```
DatasetDict({
    train: Dataset({
        features: ['corpus_id', 'text', 'labels', 'split'],
        num_rows: 8432
    })
    test: Dataset({
        features: ['corpus_id', 'text', 'labels', 'split'],
        num_rows: 942
    })
    validation: Dataset({
        features: ['corpus_id', 'text', 'labels', 'split'],
        num_rows: 924
    })
})
```

Metrics:

```
{
      "epoch": 2.2727272727272725,
      "eval_eval/0_f1-score": 0.9234567901234568,
      "eval_eval/0_precision": 0.9396984924623115,
      "eval_eval/0_recall": 0.9077669902912622,
      "eval_eval/0_support": 412.0,
      "eval_eval/1_f1-score": 0.9422718808193669,
      "eval_eval/1_precision": 0.9301470588235294,
      "eval_eval/1_recall": 0.9547169811320755,
      "eval_eval/1_support": 530.0,
      "eval_eval/accuracy": 0.9341825902335457,
      "eval_eval/macro avg_f1-score": 0.9328643354714119,
      "eval_eval/macro avg_precision": 0.9349227756429205,
      "eval_eval/macro avg_recall": 0.9312419857116688,
      "eval_eval/macro avg_support": 942.0,
      "eval_eval/mps_allocated_gb": 1.822583552,
      "eval_eval/mps_reserved_gb": 143.440986112,
      "eval_eval/weighted avg_f1-score": 0.9340427753345314,
      "eval_eval/weighted avg_precision": 0.934324543599727,
      "eval_eval/weighted avg_recall": 0.9341825902335457,
      "eval_eval/weighted avg_support": 942.0,
      "eval_loss": 0.23617032170295715,
      "eval_runtime": 42.6005,
      "eval_samples_per_second": 22.112,
      "eval_steps_per_second": 1.385,
      "step": 600
    }
```

~92/93% on key metrics