rakib730
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bert-finetuned-ner

Token Classification

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bert-finetuned-ner

This model is a fine-tuned version of bert-base-cased on the conll2003 dataset.

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training results

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

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Safetensors

Model size

0.1B params

Tensor type

F32

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Model tree for rakib730/bert-finetuned-ner

Base model

google-bert/bert-base-cased

Finetuned

(2935)

this model

Dataset used to train rakib730/bert-finetuned-ner