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product_classifier – AI Model by cnicu | AlphaNeural AI
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cnicu
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product_classifier
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transformers
pytorch
tensorboard
distilbert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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product_classifier
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6760
Accuracy: {'accuracy': 0.80125}
Precision: {'precision': 0.785989926719994}
Recall: {'recall': 0.7755906520102293}
F1 Score: {'f1': 0.7704315421053631}
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: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1 Score
0.9575
1.0
3200
0.6832
{'accuracy': 0.7978125}
{'precision': 0.7851098622896849}
{'recall': 0.7737991362724596}
{'f1': 0.771520016712035}
Framework versions
Transformers 4.28.0
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3
