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bert-tzh-med-ner – AI Model by kaishih | AlphaNeural AI
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kaishih
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bert-tzh-med-ner
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tensorboard
safetensors
bert
generated_from_trainer
zh
kaishih/CMeEE-V2
google-bert/bert-base-chinese
finetune
apache-2.0
us
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Model card
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test-ner
This model is a fine-tuned version of
bert-base-chinese
on an CMeEE-V2 dataset. It achieves the following results on the evaluation set:
Loss: 0.4423
Precision: 0.5197
Recall: 0.6287
F1: 0.5690
Accuracy: 0.8492
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.6791
1.0
938
0.4600
0.5031
0.6096
0.5513
0.8435
0.3969
2.0
1876
0.4423
0.5197
0.6287
0.5690
0.8492
Framework versions
Transformers 4.42.4
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1
