---
language: fa
pipeline_tag: text-classification
library_name: transformers
---

# QomSSLab/SubjectClassifier-v1

This repository hosts a sequence-classification head trained for text classification.

## Usage

```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

model_id = "QomSSLab/SubjectClassifier-v1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForSequenceClassification.from_pretrained(model_id)
classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)

text = "مثال از یک ورودی فارسی"
print(classifier(text))
```

## Labels

- `اخلاق`
- `تاریخ`
- `حدیث`
- `سیاسی`
- `فقه و احکام`
- `قرآن`
- `مشاوره`
- `کلام و اعتقادات`

## Metrics

## Validation Metrics

- Precision: 0.9717
- Recall: 0.9713
- F1: 0.9713
- Accuracy: 0.9713

### Per-label Breakdown

| Label | Precision | Recall | F1 | Support |
| --- | --- | --- | --- | --- |
| اخلاق | 0.9455 | 0.9598 | 0.9526 | 199 |
| تاریخ | 0.9815 | 1.0000 | 0.9907 | 53 |
| حدیث | 0.9487 | 0.9823 | 0.9652 | 113 |
| سیاسی | 1.0000 | 0.9693 | 0.9844 | 163 |
| فقه و احکام | 0.9652 | 1.0000 | 0.9823 | 222 |
| قرآن | 1.0000 | 0.9875 | 0.9937 | 80 |
| مشاوره | 0.9670 | 0.9263 | 0.9462 | 95 |
| کلام و اعتقادات | 0.9818 | 0.9558 | 0.9686 | 226 |