bert-finetuned-ner – AI Model by CzarnyRycerz | AlphaNeural AI

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CzarnyRycerz/
bert-finetuned-ner

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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

This model is a fine-tuned version of bert-base-cased on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.0658
Precision: 0.9366
Recall: 0.9520
F1: 0.9442
Accuracy: 0.9869

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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0766	1.0	1756	0.0716	0.9122	0.9359	0.9239	0.9810
0.0402	2.0	3512	0.0606	0.9266	0.9475	0.9369	0.9853
0.0248	3.0	5268	0.0586	0.9332	0.9493	0.9412	0.9869
0.01	4.0	7024	0.0658	0.9366	0.9520	0.9442	0.9869

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1