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bert-finetuned-deid-stanford – AI Model by linbin1973 | AlphaNeural AI
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linbin1973
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bert-finetuned-deid-stanford
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transformers
safetensors
bert
token-classification
generated_from_trainer
StanfordAIMI/stanford-deidentifier-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-deid-stanford
This model is a fine-tuned version of
StanfordAIMI/stanford-deidentifier-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0225
Precision: 0.9652
Recall: 0.9534
F1: 0.9593
Accuracy: 0.9959
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
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
430
0.0279
0.9276
0.9190
0.9233
0.9940
0.1053
2.0
860
0.0229
0.9590
0.9479
0.9534
0.9958
0.0179
3.0
1290
0.0225
0.9652
0.9534
0.9593
0.9959
Framework versions
Transformers 4.44.2
Pytorch 2.5.0
Datasets 2.21.0
Tokenizers 0.19.1
