readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - lst20
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: premodel
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: lst20
        type: lst20
        config: default
        split: train
        args: default
      metrics:
      - name: Precision
        type: precision
        value: 0.8533733110439704
      - name: Recall
        type: recall
        value: 0.8653846153846154
      - name: F1
        type: f1
        value: 0.8593369935367294
      - name: Accuracy
        type: accuracy
        value: 0.9477067610537897
  ---
  
  <!-- 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. -->
  
  # premodel
  
  This model is a fine-tuned version of [Geotrend/bert-base-th-cased](https://huggingface.co/Geotrend/bert-base-th-cased) on the lst20 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1761
  - Precision: 0.8534
  - Recall: 0.8654
  - F1: 0.8593
  - Accuracy: 0.9477
  
  ## 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: 5e-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: 3.0
  
  ### Training results
  
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  