This model is a fine-tuned version of bert-base-cased on the article100v7_wikigold_split dataset. It achieves the following results on the evaluation set:

Loss: 0.4325
Precision: 0.4198
Recall: 0.3217
F1: 0.3643
Accuracy: 0.8503

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	24	0.5750	0.1635	0.0267	0.0459	0.7926
No log	2.0	48	0.4594	0.3845	0.2483	0.3017	0.8393
No log	3.0	72	0.4325	0.4198	0.3217	0.3643	0.8503

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu113
Datasets 2.4.0
Tokenizers 0.11.6

DOOGLAK/Article_100v7_NER_Model_3Epochs_AUGMENTED

Article_100v7_NER_Model_3Epochs_AUGMENTED

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

DOOGLAK/
Article_100v7_NER_Model_3Epochs_AUGMENTED