deberta-v3-large-finetuned-ner-10epochs-V2 – AI Model by ABrinkmann | AlphaNeural AI

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ABrinkmann/
deberta-v3-large-finetuned-ner-10epochs-V2

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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deberta-v3-large-finetuned-ner-10epochs-V2

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: 0.0941
Precision: 0.9139
Recall: 0.9358
F1: 0.9248
Accuracy: 0.9856

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0539	1.0	2261	0.0571	0.8751	0.9304	0.9019	0.9822
0.0481	2.0	4522	0.0515	0.8794	0.9387	0.9081	0.9833
0.0362	3.0	6783	0.0502	0.8956	0.9336	0.9142	0.9841
0.0341	4.0	9044	0.0456	0.9097	0.9301	0.9198	0.9856
0.0272	5.0	11305	0.0520	0.9005	0.9451	0.9223	0.9860
0.0214	6.0	13566	0.0583	0.9069	0.9330	0.9197	0.9855
0.0162	7.0	15827	0.0684	0.9154	0.9259	0.9206	0.9854
0.0129	8.0	18088	0.0736	0.9158	0.9339	0.9248	0.9854
0.0074	9.0	20349	0.0869	0.9091	0.9355	0.9221	0.9854
0.0049	10.0	22610	0.0941	0.9139	0.9358	0.9248	0.9856

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu117
Datasets 2.13.0
Tokenizers 0.13.3