bert-finetuned-ner-cti – AI Model by thongnef | AlphaNeural AI

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thongnef/
bert-finetuned-ner-cti

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token-classification

generated_from_trainer

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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bert-finetuned-ner-cti

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

Loss: 0.1001
Precision: 0.9730
Recall: 0.9844
F1: 0.9787
Accuracy: 0.9852

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0346	1.0	1725	0.0779	0.9603	0.9788	0.9695	0.9812
0.0271	2.0	3450	0.0840	0.9588	0.9811	0.9698	0.9815
0.026	3.0	5175	0.0718	0.9686	0.9812	0.9748	0.9836
0.018	4.0	6900	0.0749	0.9687	0.9828	0.9757	0.9841
0.0136	5.0	8625	0.0872	0.9702	0.9838	0.9770	0.9847
0.0085	6.0	10350	0.0932	0.9682	0.9833	0.9757	0.9838
0.0075	7.0	12075	0.0906	0.9741	0.9836	0.9788	0.9852
0.0051	8.0	13800	0.0951	0.9727	0.9836	0.9781	0.9849
0.0034	9.0	15525	0.0990	0.9732	0.9846	0.9789	0.9851
0.0027	10.0	17250	0.1001	0.9730	0.9844	0.9787	0.9852

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0