bert-base-NER-finetuned-cv – AI Model by reyhanemyr | AlphaNeural AI

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reyhanemyr/
bert-base-NER-finetuned-cv

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-base-NER-finetuned-cv

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

Loss: 0.2286
Precision: 0.5979
Recall: 0.6200
F1: 0.6087
Accuracy: 0.9403

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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	17	0.4546	0.3763	0.1438	0.2081	0.8915
No log	2.0	34	0.3523	0.3969	0.3429	0.3680	0.9087
No log	3.0	51	0.2957	0.4062	0.5343	0.4615	0.9154
No log	4.0	68	0.2474	0.5438	0.5050	0.5237	0.9323
No log	5.0	85	0.2326	0.5383	0.6029	0.5687	0.9360
No log	6.0	102	0.2265	0.5761	0.6344	0.6038	0.9397
No log	7.0	119	0.2286	0.5979	0.6200	0.6087	0.9403

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2