hindi-bert-ner

mirfan899/hindi-bert-ner

hindi-bert-ner is a token classification model from mirfan899. 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. --

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At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Oct 21, 2023
Updated: Oct 21, 2023
SHA: 120fdfde

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Base models

Model card

From the Hugging Face model README

hindi-bert-ner

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

Loss: 0.0337
Precision: 0.8427
Recall: 0.9013
F1: 0.8710
Accuracy: 0.9919

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: 0.0003
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
0.3231	1.0	882	0.1740	0.4463	0.5576	0.4957	0.9588
0.1442	2.0	1764	0.0758	0.6599	0.7765	0.7135	0.9811
0.0472	3.0	2646	0.0337	0.8427	0.9013	0.8710	0.9919

Framework versions

Transformers 4.33.0
Pytorch 2.0.0
Datasets 2.14.5
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Oct 21, 2023
Updated: Oct 21, 2023