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bert-base-uncased-finetuned-swag – AI Model by zlxi | AlphaNeural AI
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zlxi
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bert-base-uncased-finetuned-swag
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transformers
pytorch
tensorboard
bert
multiple-choice
generated_from_trainer
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 an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6935
Accuracy: 0.4100
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
25
0.6945
0.3800
No log
2.0
50
0.6936
0.3600
No log
3.0
75
0.6935
0.4100
Framework versions
Transformers 4.26.1
Pytorch 1.12.1
Datasets 2.10.1
Tokenizers 0.13.2
