This model is a fine-tuned version of bert-base-cased on the article500v8_wikigold_split dataset. It achieves the following results on the evaluation set:

Loss: 0.1980
Precision: 0.6780
Recall: 0.7117
F1: 0.6945
Accuracy: 0.9363

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	64	0.2758	0.5405	0.5298	0.5351	0.9135
No log	2.0	128	0.2129	0.6350	0.6695	0.6518	0.9296
No log	3.0	192	0.1980	0.6780	0.7117	0.6945	0.9363

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu113
Datasets 2.4.0
Tokenizers 0.11.6

DOOGLAK/Article_500v8_NER_Model_3Epochs_UNAUGMENTED

Article_500v8_NER_Model_3Epochs_UNAUGMENTED

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

DOOGLAK/
Article_500v8_NER_Model_3Epochs_UNAUGMENTED