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DeBERTa-finetuned-ner-conll2003 – AI Model by ViktorDo | AlphaNeural AI
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ViktorDo
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DeBERTa-finetuned-ner-conll2003
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transformers
pytorch
tensorboard
deberta-v2
token-classification
generated_from_trainer
conll2003
mit
model-index
autotrain_compatible
endpoints_compatible
us
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DeBERTa-finetuned-ner-conll2003
This model is a fine-tuned version of
microsoft/deberta-v3-small
on the conll2003 dataset. It achieves the following results on the evaluation set:
Loss: 0.0406
Precision: 0.9517
Recall: 0.9643
F1: 0.9580
Accuracy: 0.9914
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0597
1.0
1756
0.0486
0.9316
0.9493
0.9404
0.9884
0.0286
2.0
3512
0.0413
0.9479
0.9606
0.9542
0.9908
0.0173
3.0
5268
0.0406
0.9517
0.9643
0.9580
0.9914
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
