This model is a fine-tuned version of bert-base-cased on the article100v2_wikigold_split dataset. It achieves the following results on the evaluation set:

Loss: 0.6054
Precision: 0.0339
Recall: 0.0005
F1: 0.0010
Accuracy: 0.7819

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	12	0.7284	0.0	0.0	0.0	0.7814
No log	2.0	24	0.6406	0.0	0.0	0.0	0.7813
No log	3.0	36	0.6054	0.0339	0.0005	0.0010	0.7819

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu113
Datasets 2.4.0
Tokenizers 0.11.6

DOOGLAK/Article_100v2_NER_Model_3Epochs_UNAUGMENTED

Article_100v2_NER_Model_3Epochs_UNAUGMENTED

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

DOOGLAK/
Article_100v2_NER_Model_3Epochs_UNAUGMENTED