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fine-tuned-MoritzLaurer-deberta-v3-base-zeroshot-v2.0-arceasy – AI Model by amritpuhan | AlphaNeural AI
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fine-tuned-MoritzLaurer-deberta-v3-base-zeroshot-v2.0-arceasy
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transformers
safetensors
deberta-v2
multiple-choice
generated_from_trainer
allenai/ai2_arc
MoritzLaurer/deberta-v3-base-zeroshot-v2.0
finetune
mit
endpoints_compatible
us
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fine-tuned-MoritzLaurer-deberta-v3-base-zeroshot-v2.0-arceasy
This model is a fine-tuned version of
MoritzLaurer/deberta-v3-base-zeroshot-v2.0
on ARC-Easy dataset. It achieves the following results on the evaluation set:
Loss: 0.9473
Accuracy: 0.7123
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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
71
1.0023
0.6947
No log
2.0
142
1.0230
0.6982
No log
3.0
213
0.9488
0.7053
No log
4.0
284
0.9037
0.7211
No log
5.0
355
0.9433
0.7123
No log
6.0
426
0.9473
0.7123
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
