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question_answering – AI Model by nikhilwani | AlphaNeural AI
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nikhilwani
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question_answering
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transformers
pytorch
distilbert
question-answering
generated_from_trainer
squad
distilbert/distilbert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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question_answering
This model is a fine-tuned version of
distilbert-base-uncased
on the squad dataset. It achieves the following results on the evaluation set:
Loss: 1.6922
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: 2e-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
No log
1.0
250
1.6142
0.9008
2.0
500
1.6113
0.9008
3.0
750
1.6922
Framework versions
Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3
