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bert-base-uncased-finetuned-swag – AI Model by gueleilo | AlphaNeural AI
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gueleilo
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bert-base-uncased-finetuned-swag
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transformers
tensorboard
safetensors
bert
multiple-choice
generated_from_trainer
swag
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 swag dataset. It achieves the following results on the evaluation set:
Loss: 1.0294
Accuracy: 0.7865
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
0.7719
1.0
4597
0.5905
0.7725
0.3799
2.0
9194
0.6167
0.7838
0.1545
3.0
13791
1.0294
0.7865
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0
