DeBERTa-finetuned-ner-copious – AI Model by ViktorDo | AlphaNeural AI

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ViktorDo/
DeBERTa-finetuned-ner-copious

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token-classification

generated_from_trainer

microsoft/deberta-v3-base

autotrain_compatible

endpoints_compatible

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DeBERTa-finetuned-ner-copious

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

Loss: 0.0499
Precision: 0.7867
Recall: 0.8333
F1: 0.8094
Accuracy: 0.9842

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	63	0.0632	0.6793	0.7383	0.7076	0.9789
No log	2.0	126	0.0507	0.7559	0.8320	0.7921	0.9837
No log	3.0	189	0.0517	0.7771	0.8306	0.8029	0.9840
No log	4.0	252	0.0517	0.7822	0.8457	0.8127	0.9839
No log	5.0	315	0.0499	0.7867	0.8333	0.8094	0.9842

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3