readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: umit_txtclass2
    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. -->
  
  # umit_txtclass2
  
  This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on a 
   full dataset at Home PC i5 9600K RTX2060 6GB.It achieves the following results on the evaluation set:
  - Loss: 0.5844
  - Accuracy: 0.9116
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  https://huggingface.co/savasy/bert-turkish-text-classification
  
  The following Turkish benchmark dataset is used for fine-tuning
  
  https://www.kaggle.com/savasy/ttc4900
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - train_batch_size: 4
  - 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
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.2855        | 1.0   | 858  | 0.6071          | 0.8986   |
  | 0.2077        | 2.0   | 1716 | 0.5425          | 0.9109   |
  | 0.112         | 3.0   | 2574 | 0.5844          | 0.9116   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  