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QA_squatdataset_nlp_model – AI Model by brijeshkumarbajpai155 | AlphaNeural AI

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brijeshkumarbajpai155/
QA_squatdataset_nlp_model

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question-answering

generated_from_trainer

google-bert/bert-base-cased

endpoints_compatible

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QA_squatdataset_nlp_model

This model is a fine-tuned version of bert-base-cased on an unknown dataset.

Model description

Model is useful for Question Answering problems

Intended uses & limitations

More information needed

Training and evaluation data

SQuAD dataset is used

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
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1