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deberta-v3-large-finetuned-context_relevance_judge – AI Model by Tung177 | AlphaNeural AI
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deberta-v3-large-finetuned-context_relevance_judge
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transformers
tensorboard
safetensors
deberta-v2
text-classification
generated_from_trainer
microsoft/deberta-v3-large
finetune
mit
autotrain_compatible
endpoints_compatible
us
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deberta-v3-large-finetuned-context_relevance_judge
This model is a fine-tuned version of
microsoft/deberta-v3-large
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 3.1305
Accuracy: 0.6627
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-06
train_batch_size: 2
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
0.992
93
1.3520
0.6686
No log
1.9973
187
2.7330
0.6625
No log
2.992
280
2.8485
0.6649
No log
3.9973
374
3.1305
0.6627
Framework versions
Transformers 4.46.3
Pytorch 2.4.0
Datasets 3.1.0
Tokenizers 0.20.3
