XLMR-ENIS-finetuned-ner-finetuned-conll_ner

svanhvit/XLMR-ENIS-finetuned-ner-finetuned-conll_ner

XLMR-ENIS-finetuned-ner-finetuned-conll_ner is a token classification model from svanhvit. 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. --

Downloads · 30 days

2% of all-time downloads

All-time downloads

561

Public

Repo size

1.5 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin496 MB · 100%

At a glance

Task: Token Classification
Library: transformers
License: agpl-3.0
Model type: xlm-roberta
Access: Public
Created: Mar 2, 2022
Updated: Oct 8, 2021
SHA: c33f6f46

Try a prompt

Datasets

mim_gold_ner

Model card

From the Hugging Face model README

XLMR-ENIS-finetuned-ner-finetuned-conll_ner

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

Loss: 0.0770
Precision: 0.8720
Recall: 0.8430
F1: 0.8573
Accuracy: 0.9858

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
0.0461	1.0	2904	0.0647	0.8588	0.8107	0.8341	0.9842
0.0244	2.0	5808	0.0704	0.8691	0.8296	0.8489	0.9849
0.0132	3.0	8712	0.0770	0.8720	0.8430	0.8573	0.9858

Framework versions

Transformers 4.11.3
Pytorch 1.9.0+cu111
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 8, 2021