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deberta-base-finetuned-aqa – AI Model by stevemobs | AlphaNeural AI
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deberta-base-finetuned-aqa
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transformers
pytorch
tensorboard
deberta
question-answering
generated_from_trainer
adversarial_qa
mit
endpoints_compatible
us
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deberta-base-finetuned-aqa
This model is a fine-tuned version of
microsoft/deberta-base
on the adversarial_qa dataset. It achieves the following results on the evaluation set:
Loss: 1.6394
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: 12
eval_batch_size: 12
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
2.1054
1.0
2527
1.6947
1.5387
2.0
5054
1.6394
Framework versions
Transformers 4.19.2
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1
