readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: shopee-ner
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # shopee-ner
  
  This model is a fine-tuned version of [cahya/xlm-roberta-base-indonesian-NER](https://huggingface.co/cahya/xlm-roberta-base-indonesian-NER) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2046
  - Precision: 0.7666
  - Recall: 0.8666
  - F1: 0.8135
  - Accuracy: 0.9320
  
  ## 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: 8
  - eval_batch_size: 8
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.2282        | 1.0   | 33750 | 0.2174          | 0.7443    | 0.8506 | 0.7939 | 0.9253   |
  | 0.1983        | 2.0   | 67500 | 0.2046          | 0.7666    | 0.8666 | 0.8135 | 0.9320   |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.1
  - Tokenizers 0.10.3
  