distilbert-base-uncased-finetuned-ner – AI Model by aburak621 | AlphaNeural AI

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aburak621/
distilbert-base-uncased-finetuned-ner

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-finetuned-ner

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

Loss: 0.0645
Precision: 0.9356
Recall: 0.9444
F1: 0.9400
Accuracy: 0.9851

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: 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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.2464	1.0	878	0.0679	0.9223	0.9248	0.9236	0.9818
0.0526	2.0	1756	0.0574	0.9290	0.9367	0.9328	0.9837
0.0274	3.0	2634	0.0594	0.9282	0.9400	0.9341	0.9843
0.0173	4.0	3512	0.0617	0.9349	0.9428	0.9388	0.9851
0.0119	5.0	4390	0.0645	0.9356	0.9444	0.9400	0.9851

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+cpu
Datasets 2.8.0
Tokenizers 0.13.2