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pii_distilbert_v3 – AI Model by giji2 | AlphaNeural AI
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giji2
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pii_distilbert_v3
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transformers
tensorboard
safetensors
distilbert
token-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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pii_distilbert_v3
This model is a fine-tuned version of
distilbert/distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0005
Precision: 0.9998
Recall: 0.9999
F1: 0.9998
Accuracy: 0.9999
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: 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
0.0015
1.0
1001
0.0009
0.9996
0.9998
0.9997
0.9998
0.0007
2.0
2002
0.0005
0.9998
0.9999
0.9998
0.9999
Framework versions
Transformers 4.36.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.15.0
