readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: roberta-tagalog-base-ner-v1
    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. -->
  
  # roberta-tagalog-base-ner-v1
  
  This model is a fine-tuned version of [jcblaise/roberta-tagalog-base](https://huggingface.co/jcblaise/roberta-tagalog-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1768
  - Precision: 0.9579
  - Recall: 0.9600
  - F1: 0.9590
  - Accuracy: 0.9744
  
  ## 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 205  | 0.2106          | 0.8855    | 0.8757 | 0.8806 | 0.9368   |
  | No log        | 2.0   | 410  | 0.1410          | 0.9242    | 0.9334 | 0.9288 | 0.9632   |
  | 0.2474        | 3.0   | 615  | 0.1511          | 0.9367    | 0.9523 | 0.9444 | 0.9674   |
  | 0.2474        | 4.0   | 820  | 0.1600          | 0.9586    | 0.9501 | 0.9543 | 0.9700   |
  | 0.017         | 5.0   | 1025 | 0.1586          | 0.9544    | 0.9534 | 0.9539 | 0.9726   |
  | 0.017         | 6.0   | 1230 | 0.1701          | 0.9461    | 0.9545 | 0.9503 | 0.9708   |
  | 0.017         | 7.0   | 1435 | 0.1703          | 0.9557    | 0.9578 | 0.9568 | 0.9732   |
  | 0.0022        | 8.0   | 1640 | 0.1733          | 0.9568    | 0.9589 | 0.9579 | 0.9740   |
  | 0.0022        | 9.0   | 1845 | 0.1772          | 0.9579    | 0.9600 | 0.9590 | 0.9732   |
  | 0.0011        | 10.0  | 2050 | 0.1768          | 0.9579    | 0.9600 | 0.9590 | 0.9744   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  