ner-deBERTa-v2-x-large – AI Model by alphaduriendur | AlphaNeural AI

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alphaduriendur/
ner-deBERTa-v2-x-large

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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ner-deBERTa-v2-x-large

This model is a fine-tuned version of microsoft/deberta-v3-base on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.3963
Precision: 0.7384
Recall: 0.7378
F1: 0.7381
Accuracy: 0.9461

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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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	Precision	Recall	F1	Accuracy
No log	1.0	219	0.4082	0.6932	0.7087	0.7009	0.9386
No log	2.0	439	0.4299	0.7467	0.6948	0.7198	0.9426
0.0094	3.0	658	0.4086	0.7435	0.7072	0.7249	0.9441
0.0094	4.0	878	0.3873	0.7426	0.7420	0.7423	0.9461
0.0054	4.99	1095	0.3963	0.7384	0.7378	0.7381	0.9461

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3