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fine-tuned-bert-large-uncased-swag – AI Model by amritpuhan | AlphaNeural AI
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amritpuhan
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fine-tuned-bert-large-uncased-swag
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transformers
safetensors
bert
multiple-choice
generated_from_trainer
swag
google-bert/bert-large-uncased
finetune
apache-2.0
endpoints_compatible
us
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fine-tuned-bert-large-uncased-swag
This model is a fine-tuned version of
bert-large-uncased
on the swag dataset. It achieves the following results on the evaluation set:
Loss: 0.9041
Accuracy: 0.8505
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: 1.5e-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: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6324
1.0
4597
0.4249
0.8428
0.3435
2.0
9194
0.4327
0.8456
0.1759
3.0
13791
0.6816
0.8475
0.0677
4.0
18388
0.9041
0.8505
Framework versions
Transformers 4.41.2
Pytorch 1.11.0
Datasets 2.19.1
Tokenizers 0.19.1
