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

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chunfengw/
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 None dataset. It achieves the following results on the evaluation set:

eval_loss: 0.0132
eval_precision: 0.9060
eval_recall: 0.8940
eval_f1: 0.9
eval_accuracy: 0.9976
eval_runtime: 10.5332
eval_samples_per_second: 234.876
eval_steps_per_second: 29.431
epoch: 1.0
step: 5568

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 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1