product_classifier / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
model-index:
  - name: product_classifier
    results: []

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