BERT_MC_OpenBookQA_w_wrong_context – AI Model by Shaier | AlphaNeural AI

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BERT_MC_OpenBookQA_w_wrong_context

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BERT_MC_OpenBookQA_w_wrong_context

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: 0.7450
Accuracy: 0.922

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: 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: 11

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3525	1.0	1859	0.2696	0.906
0.2084	2.0	3718	0.3284	0.9143
0.1263	3.0	5577	0.4205	0.9143
0.0734	4.0	7436	0.4688	0.9203
0.0437	5.0	9295	0.6266	0.9173
0.0357	6.0	11154	0.6934	0.9207
0.0264	7.0	13013	0.6947	0.92
0.0098	8.0	14872	0.6800	0.9197
0.0104	9.0	16731	0.7393	0.923
0.0067	10.0	18590	0.7846	0.9217
0.0034	11.0	20449	0.7450	0.922

Framework versions

Transformers 4.21.3
Pytorch 1.12.1
Datasets 2.5.1
Tokenizers 0.11.0