ner_model – AI Model by RachelCX | AlphaNeural AI | AlphaNeural AI

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RachelCX/
ner_model

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token-classification

generated_from_trainer

hfl/chinese-bert-wwm-ext

autotrain_compatible

endpoints_compatible

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ner_model

This model is a fine-tuned version of hfl/chinese-bert-wwm-ext on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0311
Precision: 1.0000
Recall: 1.0000
F1: 1.0000
Accuracy: 1.0000

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: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.031	1.0	15055	0.0317	1.0000	1.0000	1.0000	1.0000
0.031	2.0	30110	0.0313	1.0000	1.0000	1.0000	1.0000
0.031	3.0	45165	0.0312	1.0000	1.0000	1.0000	1.0000
0.031	4.0	60220	0.0311	1.0000	1.0000	1.0000	1.0000
0.031	5.0	75275	0.0311	1.0000	1.0000	1.0000	1.0000

Framework versions

Transformers 4.50.0
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1