readme: ---
  license: gpl-3.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-tagalog-base-uncased-WWM-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. -->
  
  # bert-tagalog-base-uncased-WWM-ner-v1
  
  This model is a fine-tuned version of [jcblaise/bert-tagalog-base-uncased-WWM](https://huggingface.co/jcblaise/bert-tagalog-base-uncased-WWM) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2838
  - Precision: 0.9280
  - Recall: 0.9153
  - F1: 0.9216
  - Accuracy: 0.9509
  
  ## 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  | 0.4812          | 0.6267    | 0.6367 | 0.6317 | 0.8502   |
  | No log        | 2.0   | 410  | 0.2683          | 0.8322    | 0.8289 | 0.8305 | 0.9228   |
  | 0.4348        | 3.0   | 615  | 0.2377          | 0.9020    | 0.8846 | 0.8932 | 0.9398   |
  | 0.4348        | 4.0   | 820  | 0.2566          | 0.8906    | 0.8977 | 0.8941 | 0.9439   |
  | 0.0549        | 5.0   | 1025 | 0.2587          | 0.9249    | 0.9034 | 0.9140 | 0.9469   |
  | 0.0549        | 6.0   | 1230 | 0.2616          | 0.8988    | 0.9136 | 0.9061 | 0.9469   |
  | 0.0549        | 7.0   | 1435 | 0.2716          | 0.9102    | 0.9164 | 0.9133 | 0.9497   |
  | 0.011         | 8.0   | 1640 | 0.2929          | 0.9317    | 0.9147 | 0.9231 | 0.9507   |
  | 0.011         | 9.0   | 1845 | 0.2819          | 0.9280    | 0.9153 | 0.9216 | 0.9512   |
  | 0.0043        | 10.0  | 2050 | 0.2838          | 0.9280    | 0.9153 | 0.9216 | 0.9509   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  