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

Loss: 0.3602
Precision: 0.6222
Recall: 0.6439
F1: 0.6329
Accuracy: 0.9038

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.9117	1.0	784	0.4198	0.5691	0.5948	0.5817	0.8893
0.4089	2.0	1568	0.3602	0.6222	0.6439	0.6329	0.9038

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

nelsenputra/my_awesome_id_nergrit_corpus_model

my_awesome_id_nergrit_corpus_model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nelsenputra/
my_awesome_id_nergrit_corpus_model