my_awesome_qa_model – AI Model by balchid | AlphaNeural AI

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my_awesome_qa_model

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google-bert/bert-base-uncased

endpoints_compatible

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my_awesome_qa_model

This model is a fine-tuned version of bert-base-uncased on the squad dataset. It achieves the following results on the evaluation set:

Loss: 0.0082

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
0.5682	1.0	1250	0.5403
0.7379	2.0	2500	0.3208
0.4839	3.0	3750	0.1690
0.3227	4.0	5000	0.0984
0.2188	5.0	6250	0.0498
0.1484	6.0	7500	0.0341
0.1065	7.0	8750	0.0199
0.0796	8.0	10000	0.0127
0.0599	9.0	11250	0.0093
0.0484	10.0	12500	0.0082

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0