XLMR-ENIS-finetuned-ner

bergurth/XLMR-ENIS-finetuned-ner

XLMR-ENIS-finetuned-ner is a token classification model from bergurth. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as agpl-3.0.

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

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At a glance

Task: Token Classification
Library: transformers
License: agpl-3.0
Model type: xlm-roberta
Access: Public
Created: Mar 2, 2022
Updated: Oct 5, 2021
SHA: c09cd7b3

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Datasets

mim_gold_ner

Model card

From the Hugging Face model README

XLMR-ENIS-finetuned-ner

This model is a fine-tuned version of vesteinn/XLMR-ENIS on the mim_gold_ner dataset. It achieves the following results on the evaluation set:

Loss: 0.0938
Precision: 0.8619
Recall: 0.8384
F1: 0.8500
Accuracy: 0.9831

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
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	Precision	Recall	F1	Accuracy
0.0574	1.0	2904	0.0983	0.8374	0.8061	0.8215	0.9795
0.0321	2.0	5808	0.0991	0.8525	0.8235	0.8378	0.9811
0.0179	3.0	8712	0.0938	0.8619	0.8384	0.8500	0.9831

Framework versions

Transformers 4.11.2
Pytorch 1.9.0+cu102
Datasets 1.12.1
Tokenizers 0.10.3

Task: Token Classification
Library: transformers
Type: xlm-roberta
License: agpl-3.0
Created: Mar 2, 2022
Updated: Oct 5, 2021