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bert-base-uncased-finetuned-swag – AI Model by jhoonk | AlphaNeural AI
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jhoonk
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bert-base-uncased-finetuned-swag
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transformers
pytorch
tensorboard
bert
multiple-choice
generated_from_trainer
swag
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 swag dataset. It achieves the following results on the evaluation set:
Loss: 1.0337
Accuracy: 0.7888
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
0.7451
1.0
4597
0.5944
0.7696
0.3709
2.0
9194
0.6454
0.7803
0.1444
3.0
13791
1.0337
0.7888
Framework versions
Transformers 4.18.0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1
