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bert-tzh-med-classification – AI Model by kaishih | AlphaNeural AI
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kaishih
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bert-tzh-med-classification
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safetensors
bert
generated_from_trainer
ckiplab/bert-base-chinese
finetune
gpl-3.0
us
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results
This model is a fine-tuned version of
ckiplab/bert-base-chinese
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2556
Accuracy: 0.9277
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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.3077
1.0
2528
0.2888
0.9102
0.2328
2.0
5056
0.2631
0.9207
0.143
3.0
7584
0.2556
0.9277
Framework versions
Transformers 4.42.4
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1
