This model is a fine-tuned version of google/mobilebert-uncased on the id_nergrit_corpus dataset. It achieves the following results on the evaluation set:

Loss: 0.3800
Precision: 0.6700
Recall: 0.6136
F1: 0.6406
Accuracy: 0.8974

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
0.6239	1.0	1567	0.4989	0.5842	0.4877	0.5316	0.8688
0.5356	2.0	3134	0.4003	0.6368	0.5879	0.6113	0.8905
0.4035	3.0	4701	0.3800	0.6700	0.6136	0.6406	0.8974

Framework versions

Transformers 4.29.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3

kstn/mobilebert-uncased-finetuned-ner

mobilebert-uncased-finetuned-ner

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

kstn/
mobilebert-uncased-finetuned-ner