---
license: cc-by-nc-sa-4.0
library_name: transformers
pipeline_tag: token-classification
widget:
- text: "Do you think that looks like a cat? Answer: I don't think so."
- example_title: "cat"
---
### xlm-roberta-base for token classification, specifically fine-tuned for question-answer extraction for English

This is the `xlm-roberta-base`, fine-tuned on manually annotated Finnish data and ChatGPT-annotated data.
### Hyperparameters
```
batch_size = 8
epochs = 10 (trained for less)
base_LM_model = "xlm-roberta-base"
max_seq_len = 512
learning_rate = 5e-5
```
### Performance
```
Accuracy = 0.88
Question F1 = 0.77 
Answer F1 = 0.81
```

### Usage

To get the best question-answer pairs use the huggingface pipeline with no aggregation strategy and do some post-processing like in this [script](https://github.com/TurkuNLP/register-qa/blob/main/token-classification/scripts/extract_qa_en_no_entropy.py).

## Citing

Citing information coming soon!