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--- |
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license: cc-by-nc-sa-4.0 |
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library_name: transformers |
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pipeline_tag: token-classification |
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widget: |
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- text: "Do you think that looks like a cat? Answer: I don't think so." |
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- example_title: "cat" |
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--- |
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### xlm-roberta-base for token classification, specifically fine-tuned for question-answer extraction for English |
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This is the `xlm-roberta-base`, fine-tuned on manually annotated Finnish data and ChatGPT-annotated data. |
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### Hyperparameters |
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``` |
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batch_size = 8 |
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epochs = 10 (trained for less) |
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base_LM_model = "xlm-roberta-base" |
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max_seq_len = 512 |
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learning_rate = 5e-5 |
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``` |
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### Performance |
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``` |
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Accuracy = 0.88 |
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Question F1 = 0.77 |
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Answer F1 = 0.81 |
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``` |
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### Usage |
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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). |
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## Citing |
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Citing information coming soon! |
