qa_model – AI Model by netgvarun2005 | AlphaNeural AI

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netgvarun2005/
qa_model

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distilbert/distilbert-base-uncased

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qa_model

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.2864

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
No log	1.0	403	1.6619
2.4962	2.0	806	1.5064
1.3281	3.0	1209	1.5355
0.943	4.0	1612	1.6105
0.6258	5.0	2015	1.7803
0.6258	6.0	2418	1.8905
0.3992	7.0	2821	2.0605
0.2949	8.0	3224	2.2018
0.2103	9.0	3627	2.2359
0.1716	10.0	4030	2.2864

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0