Xlm Roberta Large Manifesto

🚀 xlm-roberta-large-manifesto

An xlm-roberta-large model fine - tuned on multilingual data for text classification.

🚀 Quick Start

The xlm-roberta-large-manifesto is an xlm-roberta-large model finetuned on multilingual training data labeled using the Manifesto Project's coding scheme. It uses Version 2020b (December 23, 2020) of the Manifesto Project Dataset Codebook.

💻 Usage Examples

Basic Usage

from transformers import AutoTokenizer, pipeline

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

text = "We will place an immediate 6 - month halt on the finance driven closure of beds and wards, and set up an independent audit of needs and facilities."
pipe(text)

Gated access

⚠️ Important Note

Due to the 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.

📚 Documentation

Model performance

The model was evaluated on a test set of 305141 examples, which were split in a stratified manner, where for every label, 20% of all occurences were randomly selected. Metrics (precision, recall and F1 - score are weighted macro averages):

Language - specific metrics:

Debugging and issues

💡 Usage Tip

This architecture uses the sentencepiece tokenizer. In order to run the model before transformers==4.27 you need to install it manually.

📄 License

This project is licensed under the MIT license.