readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: my_ner_model1_2_split_by_sentence_
    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. -->
  
  # my_ner_model1_2_split_by_sentence_
  
  This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2257
  - Precision: 0.6377
  - Recall: 0.7644
  - F1: 0.6953
  - Accuracy: 0.9401
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 427  | 0.2342          | 0.5265    | 0.6923 | 0.5981 | 0.9264   |
  | 0.3433        | 2.0   | 854  | 0.1959          | 0.6024    | 0.7397 | 0.6640 | 0.9364   |
  | 0.1686        | 3.0   | 1281 | 0.2085          | 0.6068    | 0.7608 | 0.6752 | 0.9376   |
  | 0.1241        | 4.0   | 1708 | 0.2198          | 0.6376    | 0.7591 | 0.6931 | 0.9398   |
  | 0.0912        | 5.0   | 2135 | 0.2257          | 0.6377    | 0.7644 | 0.6953 | 0.9401   |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu102
  - Datasets 2.7.1
  - Tokenizers 0.12.1
  