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llm-deberta-v3-swag – AI Model by paulovsantanas | AlphaNeural AI
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llm-deberta-v3-swag
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transformers
tensorboard
safetensors
deberta-v2
multiple-choice
generated_from_trainer
en
swag
microsoft/deberta-v3-base
finetune
mit
model-index
endpoints_compatible
us
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llm-deberta-v3-swag
This model is a fine-tuned version of
microsoft/deberta-v3-base
on the SWAG dataset. It achieves the following results on the evaluation set:
Loss: 0.7839
Accuracy: 0.8680
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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
Training results
Framework versions
Transformers 4.36.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0
