multipleChoice – AI Model by Galvanlezzo | AlphaNeural AI

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multipleChoice

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multiple-choice

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bert-finetuned-10Epochs64Batch

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

Loss: 0.6931
Accuracy: 0.4993

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: 5e-05
train_batch_size: 64
eval_batch_size: 64
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	Accuracy
0.6962	1.0	569	0.6931	0.5094
0.6969	2.0	1138	0.6931	0.5062
0.6959	3.0	1707	0.6931	0.5106
0.6959	4.0	2276	0.6931	0.4975
0.6948	5.0	2845	0.6931	0.5109
0.6944	6.0	3414	0.6931	0.4948
0.695	7.0	3983	0.6931	0.5092
0.694	8.0	4552	0.6931	0.5054
0.6941	9.0	5121	0.6931	0.4998
0.6944	10.0	5690	0.6931	0.4993

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2