xlnet-lg-cased-ms-ner-test – AI Model by nxaliao | AlphaNeural AI

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nxaliao/
xlnet-lg-cased-ms-ner-test

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token-classification

generated_from_trainer

xlnet/xlnet-large-cased

autotrain_compatible

endpoints_compatible

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xlnet-lg-cased-ms-ner-test

This model is a fine-tuned version of xlnet-large-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1308
Precision: 0.8828
Recall: 0.9077
F1: 0.8951
Accuracy: 0.9814

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
0.137	1.0	3615	0.1313	0.7971	0.7986	0.7979	0.9663
0.0761	2.0	7230	0.0894	0.8564	0.8773	0.8667	0.9781
0.0459	3.0	10845	0.0946	0.8718	0.8918	0.8817	0.9803
0.021	4.0	14460	0.1091	0.8795	0.9017	0.8905	0.9808
0.013	5.0	18075	0.1308	0.8828	0.9077	0.8951	0.9814

Framework versions

Transformers 4.39.3
Pytorch 1.12.0
Datasets 2.18.0
Tokenizers 0.15.2