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# Model Card

## Model Description
This is an **xlm-roberta-large** model finetuned on English training data labelled with the 10 major level codes from the LiSST thesaurus:

1. **Demographics**: DEMOGRAPHY, LIFE EVENTS, IDENTITY  
2. **Environment**: ENVIRONMENT (including HOME)  
3. **Health**: HEALTH & CARE  
4. **Work**: WORK & EMPLOYMENT (including TRAINING)  
5. **Education**: EDUCATION & QUALIFICATION  
6. **Network**: FAMILY & SOCIAL NETWORK  
7. **Values**: ATTITUDES, VALUES  
8. **Policy**: PUBLIC POLICY  
9. **Time use**: TIME USE, LEISURE  
10. **Income**: INCOME AND CONSUMPTION  

---

## How to Use the Model

```python
from transformers import AutoTokenizer, pipeline

tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-large")
pipe = pipeline(
    model="poltextlab/ontolisst_major_v1_xlm-roberta-large_8_5e-06_128",
    task="text-classification",
    tokenizer=tokenizer,
    use_fast=False,
    token="<your_hf_read_only_token>"
)

text = "Apart from yourself (and your husband/wife/partner), does anyone else living in your household make a contribution towards the cost of the accommodation?
pipe(text)
```

## Gated Access

This model requires gated access. You must pass the token parameter when loading the model.
In earlier versions of the Transformers package, you may need to use the use_auth_token parameter instead.

## Model Performance
The model was evaluated on a test set of **1,627 English examples**.

- **Accuracy**: 0.82
- **Precision**: 0.82
- **Recall**: 0.82
- **Weighted Average F1-score**: 0.82  

### Classification Report

| Label | Precision | Recall | F1-score | Support |
|-------|-----------|--------|----------|---------|
| 1 (Demographics) | 0.70 | 0.52 | 0.60 | 117 |
| 2 (Environment) | 0.79 | 0.72 | 0.75 | 109 |
| 3 (Health) | 0.89 | 0.94 | 0.92 | 679 |
| 4 (Work) | 0.83 | 0.84 | 0.84 | 127 |
| 5 (Education) | 0.81 | 0.83 | 0.82 | 111 |
| 6 (Network) | 0.77 | 0.87 | 0.82 | 241 |
| 7 (Values) | 0.72 | 0.70 | 0.71 | 138 |
| 8 (Policy) | 0.89 | 0.31 | 0.46 | 26 |
| 9 (Time use) | 0.75 | 0.26 | 0.39 | 23 |
| 10 (Income) | 0.68 | 0.71 | 0.70 | 56 |