README.md

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

# QomSSLab/Verdict_Splitter

This repository hosts an XLM-RoBERTa token-classification head trained.

## Usage

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

model_id = "QomSSLab/Verdict_Splitter"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForTokenClassification.from_pretrained(model_id)
tagger = pipeline("token-classification", model=model, tokenizer=tokenizer, aggregation_strategy="simple")

text = "مثال از یک ورودی فارسی"
for entity in tagger(text):
    print(entity)
```

## Labels

- `O`
- `استدلال`
- `تصمیم`
- `خارج`
- `خلع`
- `مقدمه`
- `پایانی`

## Metrics

## Validation Metrics

- Precision: 0.7430
- Recall: 0.8457
- F1: 0.7910
- Accuracy: 0.9545

### Per-label Breakdown

| Label | Precision | Recall | F1 | Support |
| --- | --- | --- | --- | --- |
| O | 0.8468 | 0.7995 | 0.8225 | 394 |
| استدلال | 0.9754 | 0.8776 | 0.9239 | 6635 |
| تصمیم | 0.9917 | 0.9608 | 0.9760 | 5361 |
| خارج | 1.0000 | 1.0000 | 1.0000 | 0 |
| خلع | 1.0000 | 1.0000 | 1.0000 | 0 |
| مقدمه | 0.9279 | 0.9982 | 0.9618 | 10871 |
| پایانی | 0.9728 | 0.9902 | 0.9814 | 1732 |