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name-classifier – AI Model by mwarchalowski | AlphaNeural AI
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name-classifier
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transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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test-trainer
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0804
Accuracy: 0.9849
F1: 0.9788
Precision: 0.9743
Recall: 0.9833
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: 5e-05
train_batch_size: 600
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.0271
1.0
703
0.0577
0.9845
0.9782
0.9760
0.9803
0.0247
2.0
1406
0.0736
0.9850
0.9791
0.9719
0.9864
0.012
3.0
2109
0.0804
0.9849
0.9788
0.9743
0.9833
Framework versions
Transformers 4.38.2
Pytorch 2.2.0
Datasets 2.18.0
Tokenizers 0.15.2
