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scostiniano/
bert-tagalog-base-uncased-ner-v1

Name: bert-tagalog-base-uncased-ner-v1
Availability: InStock

generated_from_trainer

gpl-3.0

autotrain_compatible

endpoints_compatible

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Description

The dataset consists of 148 Filipino storytelling books, 5,005 total sentences, 45,792 total tokens, and 5,646 unique tokens.
This NER model only supports the Filipino language and does not include proper nouns, verbs, adjectives, and adverbs as of the moment
The input must undergo preprocessing. Soon I will upload the code to GitHub for preprocessing the input
To replicate the preprocessed input use this example as a guide
Input: "May umaapoy na bahay "
Preprocessed Input: "apoy bahay"

bert-tagalog-base-uncased-ner-v1

This model is a fine-tuned version of jcblaise/bert-tagalog-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2824
Precision: 0.9091
Recall: 0.8988
F1: 0.9039
Accuracy: 0.9488

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	205	0.5311	0.6465	0.5458	0.5919	0.8387
No log	2.0	410	0.3052	0.7736	0.7811	0.7774	0.9110
0.4693	3.0	615	0.2531	0.8493	0.8363	0.8427	0.9319
0.4693	4.0	820	0.2384	0.8755	0.8715	0.8735	0.9402
0.064	5.0	1025	0.2671	0.8909	0.8823	0.8866	0.9435
0.064	6.0	1230	0.2527	0.8864	0.8920	0.8892	0.9459
0.064	7.0	1435	0.2708	0.9088	0.9011	0.9049	0.9491
0.0111	8.0	1640	0.2733	0.8992	0.8977	0.8984	0.9490
0.0111	9.0	1845	0.2765	0.8991	0.8965	0.8978	0.9485
0.0037	10.0	2050	0.2824	0.9091	0.8988	0.9039	0.9488

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2

scostiniano/bert-tagalog-base-uncased-ner-v1

Description

bert-tagalog-base-uncased-ner-v1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

scostiniano/
bert-tagalog-base-uncased-ner-v1