readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: model_from_berturk_1401_v2
    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. -->
  
  # model_from_berturk_1401_v2
  
  This model is a fine-tuned version of [Buseak/model_from_berturk_1401](https://huggingface.co/Buseak/model_from_berturk_1401) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1542
  - Precision: 0.9414
  - Recall: 0.9356
  - F1: 0.9385
  - Accuracy: 0.9569
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 244  | 0.2277          | 0.9129    | 0.9058 | 0.9094 | 0.9362   |
  | No log        | 2.0   | 488  | 0.1855          | 0.9275    | 0.9204 | 0.9240 | 0.9472   |
  | 0.2477        | 3.0   | 732  | 0.1602          | 0.9403    | 0.9315 | 0.9359 | 0.9554   |
  | 0.2477        | 4.0   | 976  | 0.1542          | 0.9414    | 0.9356 | 0.9385 | 0.9569   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  