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Atheer174
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Products_NER

Token Classification
Transformers
PyTorch
bert
Generated from Trainer
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Products_NER / README.md
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metadata
license: mit
base_model: dslim/bert-base-NER
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: Products_NER
    results: []

Products_NER

This model is a fine-tuned version of dslim/bert-base-NER on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0022
  • Precision: 0.9991
  • Recall: 0.9992
  • F1: 0.9992
  • Accuracy: 0.9996

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
0.0051 1.0 2470 0.0035 0.9981 0.9986 0.9984 0.9992
0.0016 2.0 4940 0.0022 0.9991 0.9992 0.9992 0.9996

Framework versions

  • Transformers 4.33.2
  • Pytorch 1.13.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.13.3