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QA_model4 – AI Model by MattNandavong | AlphaNeural AI

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MattNandavong/
QA_model4

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question-answering

generated_from_trainer

google-bert/bert-base-uncased

endpoints_compatible

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QA_model4

This model is a fine-tuned version of bert-base-uncased on an unknown 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Framework versions

Transformers 4.40.0
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1