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deberta-v3-base-finetuned-t_refund – AI Model by Gregorig | AlphaNeural AI
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Gregorig
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deberta-v3-base-finetuned-t_refund
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transformers
tensorboard
safetensors
deberta-v2
text-classification
generated_from_trainer
microsoft/deberta-v3-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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deberta-v3-base-finetuned-t_refund
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: 0.4533
Accuracy: 0.97
F1: 0.9714
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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.6724
1.0
26
0.6274
0.955
0.9330
0.4383
2.0
52
0.3402
0.94
0.9499
0.2518
3.0
78
0.3444
0.975
0.9767
0.1072
4.0
104
0.4791
0.975
0.9756
0.1466
5.0
130
0.4533
0.97
0.9714
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Tokenizers 0.19.1
