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distilbert-base-uncased_address_model – AI Model by Sunmar | AlphaNeural AI
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Sunmar
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distilbert-base-uncased_address_model
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transformers
safetensors
distilbert
token-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert-base-uncased_address_model
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: 0.2443
Precision: 0.8448
Recall: 0.8486
F1: 0.8467
Accuracy: 0.9184
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: 5
eval_batch_size: 5
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.3025
1.0
2400
0.2685
0.8215
0.8295
0.8255
0.9066
0.2398
2.0
4800
0.2443
0.8448
0.8486
0.8467
0.9184
Framework versions
Transformers 4.49.0.dev0
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0
