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bert-finetuned-ner – AI Model by lynn610 | AlphaNeural AI
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lynn610
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bert-finetuned-ner
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-chinese
finetune
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-ner
This model is a fine-tuned version of
bert-base-chinese
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1158
Precision: 0.7635
Recall: 0.7577
F1: 0.7606
Accuracy: 0.9626
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.1101
1.0
1875
0.1007
0.7357
0.7458
0.7407
0.9610
0.0796
2.0
3750
0.1003
0.76
0.7530
0.7565
0.9627
0.0538
3.0
5625
0.1158
0.7635
0.7577
0.7606
0.9626
Framework versions
Transformers 4.40.2
Pytorch 2.3.0
Datasets 2.18.0
Tokenizers 0.19.1
