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expenses-policy – AI Model by pradhap2 | AlphaNeural AI
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pradhap2
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expenses-policy
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transformers
pytorch
safetensors
deberta-v2
text-classification
generated_from_trainer
microsoft/deberta-v3-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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expenses-policy
This model is a fine-tuned version of
microsoft/deberta-v3-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6933
Accuracy: 0.492
F1: 0.3245
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: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.7028
1.0
500
0.6930
0.508
0.3423
0.6946
2.0
1000
0.6933
0.492
0.3245
Framework versions
Transformers 4.56.0
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0
