xlm-roberta-base-finetuned-panx-de

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xlm-roberta-base-finetuned-panx-de

This model is a fine-tuned version of xlm-roberta-base on the xtreme dataset. It achieves the following results on the evaluation set:

• Loss: 0.1569
• F1: 0.8638

Model description

Multilingual Named Entity Recognition across several languages

For this project's token classification, I built a unique custom model head and the WikiANN or PAN-X.2, which is a subset of the Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark, was applied. This project was completed for a customer based in switzerland, where the four languages that are most frequently spoken are German (62.9% of articles), French (22.9%), Italian (8.4%), and English (5.9%).

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 24
• eval_batch_size: 24
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.0
• Tokenizers 0.13.2