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v3-Large-mnli – AI Model by NDugar | AlphaNeural AI
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NDugar
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v3-Large-mnli
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transformers
pytorch
safetensors
deberta-v2
text-classification
deberta-v1
deberta-mnli
zero-shot-classification
en
microsoft/deberta-v3-large
finetune
mit
autotrain_compatible
endpoints_compatible
us
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This model is a fine-tuned version of
microsoft/deberta-v3-large
on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
Loss: 0.4103
Accuracy: 0.9175
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 6e-06
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
lr_scheduler_warmup_steps: 50
num_epochs: 2.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.3631
1.0
49088
0.3129
0.9130
0.2267
2.0
98176
0.4157
0.9153
Framework versions
Transformers 4.13.0.dev0
Pytorch 1.10.0
Datasets 1.15.2.dev0
Tokenizers 0.10.3
