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qa_model – AI Model by therajmaurya | AlphaNeural AI
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therajmaurya
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qa_model
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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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qa_model
This model is a fine-tuned version of
google-bert/bert-base-uncased
on the swag dataset. It achieves the following results on the evaluation set:
Loss: 1.0121
Accuracy: 0.7917
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
0.7622
1.0
4597
0.6089
0.7635
0.3862
2.0
9194
0.6362
0.7888
0.1407
3.0
13791
1.0121
0.7917
Framework versions
Transformers 4.40.0
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1
