deberta-v3-NER-ind – AI Model by Venkatesh4342 | AlphaNeural AI

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Venkatesh4342/
deberta-v3-NER-ind

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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deberta-v3-NER-ind

This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1461
Precision: 0.7969
Recall: 0.8346
F1: 0.8153
Accuracy: 0.9531

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 3
total_train_batch_size: 96
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1757	0.4	1000	0.1635	0.7737	0.8197	0.7960	0.9481
0.161	0.8	2000	0.1567	0.7794	0.8260	0.8020	0.9502
0.1365	1.2	3000	0.1517	0.7919	0.8321	0.8115	0.9522
0.1325	1.59	4000	0.1468	0.7947	0.8349	0.8143	0.9536
0.1302	1.99	5000	0.1461	0.7969	0.8346	0.8153	0.9531

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3