readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - turkish-multiclass-dataset
  metrics:
  - f1
  model-index:
  - name: distilbert-base-turkish-cased-finetuned-emotion
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: turkish-multiclass-dataset
        type: turkish-multiclass-dataset
        config: TurkishMulticlassDataset
        split: train
        args: TurkishMulticlassDataset
      metrics:
      - name: F1
        type: f1
        value:
          f1: 0.8276613385259164
  ---
  
  <!-- 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. -->
  
  # distilbert-base-turkish-cased-finetuned-emotion
  
  This model is a fine-tuned version of [dbmdz/distilbert-base-turkish-cased](https://huggingface.co/dbmdz/distilbert-base-turkish-cased) on the turkish-multiclass-dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4861
  - F1: {'f1': 0.8276613385259164}
  
  ## 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: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1                         |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------------:|
  | 0.2578        | 1.0   | 313  | 0.5459          | {'f1': 0.8212239281513611} |
  | 0.381         | 2.0   | 626  | 0.4861          | {'f1': 0.8276613385259164} |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  