Article_50v1_NER_Model_3Epochs_AUGMENTED

DOOGLAK/Article_50v1_NER_Model_3Epochs_AUGMENTED

Article_50v1_NER_Model_3Epochs_AUGMENTED is a token classification model from DOOGLAK. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.

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

Downloads · 30 days

21% of all-time downloads

All-time downloads

Public

Repo size

1.3 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin431 MB · 100%

At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Aug 11, 2022
Updated: Aug 11, 2022
SHA: 89561012

Try a prompt

Datasets

article50v1_wikigold_split

Model card

From the Hugging Face model README

Article_50v1_NER_Model_3Epochs_AUGMENTED

This model is a fine-tuned version of bert-base-cased on the article50v1_wikigold_split dataset. It achieves the following results on the evaluation set:

Loss: 0.4554
Precision: 0.2880
Recall: 0.1268
F1: 0.1761
Accuracy: 0.8302

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: 8
eval_batch_size: 8
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
No log	1.0	29	0.5376	0.1806	0.0259	0.0453	0.7947
No log	2.0	58	0.4930	0.2471	0.0789	0.1196	0.8157
No log	3.0	87	0.4554	0.2880	0.1268	0.1761	0.8302

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu113
Datasets 2.4.0
Tokenizers 0.11.6

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Aug 11, 2022
Updated: Aug 11, 2022