pii-ner-encoder_deberta – AI Model by Xyren2005 | AlphaNeural AI

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Xyren2005/
pii-ner-encoder_deberta

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token-classification

generated_from_trainer

microsoft/deberta-v3-base

endpoints_compatible

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encoder_deberta

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: 0.0614
F1: 0.9372

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: 16
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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
lr_scheduler_warmup_steps: 4640
num_epochs: 8

Training results

Training Loss	Epoch	Step	F1	Validation Loss
0.6702	1.0	2901	0.8350	0.1344
0.3783	2.0	5802	0.9054	0.0811
0.2713	3.0	8703	0.9190	0.0649
0.2137	4.0	11604	0.9264	0.0611
0.1863	5.0	14505	0.9312	0.0572
0.1400	6.0	17406	0.9343	0.0610
0.1279	7.0	20307	0.9369	0.0594
0.1059	8.0	23208	0.0614	0.9372

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.8.3
Tokenizers 0.22.2