multilingual-xlm-roberta-for-ner

sedaorcin/multilingual-xlm-roberta-for-ner

multilingual-xlm-roberta-for-ner is a token classification model from sedaorcin. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Token Classification
Library: transformers
License: mit
Model type: xlm-roberta
Access: Public
Created: May 9, 2024
Updated: May 10, 2024
SHA: 6eadf338

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Model card

From the Hugging Face model README

multilingual-xlm-roberta-for-ner

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

Loss: 0.1370
F1: 0.8653

Model description

More information needed

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.265	1.0	525	0.1523	0.8249
0.1281	2.0	1050	0.1402	0.8554
0.0818	3.0	1575	0.1370	0.8653

Framework versions

Transformers 4.28.0
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: xlm-roberta
License: mit
Created: May 9, 2024
Updated: May 10, 2024