IceBERT-ner

vesteinn/IceBERT-ner

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

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

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Base models

vesteinn/IceBERT

Datasets

mim_gold_ner

Model card

From the Hugging Face model README

IceBERT-finetuned-ner

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

Loss: 0.0347
Precision: 0.9352
Recall: 0.9440
F1: 0.9396
Accuracy: 0.9920

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
0.0568	1.0	2929	0.0386	0.9114	0.9162	0.9138	0.9897
0.0325	2.0	5858	0.0325	0.9300	0.9363	0.9331	0.9912
0.0184	3.0	8787	0.0347	0.9352	0.9440	0.9396	0.9920

Framework versions

Transformers 4.11.0
Pytorch 1.9.0+cu102
Datasets 1.12.1
Tokenizers 0.10.3

Task: Token Classification
Library: transformers
Type: roberta
License: gpl-3.0
Created: Mar 2, 2022
Updated: Sep 11, 2023