This model is a fine-tuned version of bert-base-cased on the article50v6_wikigold_split dataset. It achieves the following results on the evaluation set:

Loss: 0.7622
Precision: 0.0
Recall: 0.0
F1: 0.0
Accuracy: 0.7773

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	7	0.9429	0.1579	0.0015	0.0029	0.7769
No log	2.0	14	0.7845	0.0	0.0	0.0	0.7773
No log	3.0	21	0.7622	0.0	0.0	0.0	0.7773

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu113
Datasets 2.4.0
Tokenizers 0.11.6

DOOGLAK/Article_50v6_NER_Model_3Epochs_UNAUGMENTED

Article_50v6_NER_Model_3Epochs_UNAUGMENTED

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

DOOGLAK/
Article_50v6_NER_Model_3Epochs_UNAUGMENTED