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bert-base-uncased-finetuned-swag – AI Model by Benlitzen43 | AlphaNeural AI
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Benlitzen43
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bert-base-uncased-finetuned-swag
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transformers
pytorch
bert
multiple-choice
generated_from_trainer
cosmos_qa
google-bert/bert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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bert-base-uncased-finetuned-swag
This model is a fine-tuned version of
bert-base-uncased
on the cosmos_qa dataset. It achieves the following results on the evaluation set:
Loss: 3.2446
Accuracy: 0.5564
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.0929
1.0
6316
1.0877
0.5404
0.6544
2.0
12632
1.4658
0.5719
0.3397
3.0
18948
3.2446
0.5564
Framework versions
Transformers 4.32.1
Pytorch 2.1.1+cu121
Datasets 2.12.0
Tokenizers 0.13.2
