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

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AlexanderPeter/
bert-finetuned-ner

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token-classification

generated_from_trainer

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:

eval_loss: 0.0593
eval_precision: 0.9293
eval_recall: 0.9485
eval_f1: 0.9388
eval_accuracy: 0.9858
eval_runtime: 120.5431
eval_samples_per_second: 26.97
eval_steps_per_second: 3.376
epoch: 2.0
step: 3512

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

Framework versions

Transformers 4.19.2
Pytorch 1.11.0+cpu
Datasets 2.2.2
Tokenizers 0.12.1