readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: rubert-tiny2_finetuned_emotion_experiment_augmented_anger_fear
    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. -->
  
  # rubert-tiny2_finetuned_emotion_experiment_augmented_anger_fear
  
  This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4049
  - Accuracy: 0.8779
  - F1: 0.8775
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 40
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.3097        | 1.0   | 69   | 1.1369          | 0.6628   | 0.6210 |
  | 0.949         | 2.0   | 138  | 0.7114          | 0.8225   | 0.8202 |
  | 0.6288        | 3.0   | 207  | 0.5147          | 0.8507   | 0.8494 |
  | 0.4724        | 4.0   | 276  | 0.4424          | 0.8643   | 0.8634 |
  | 0.3912        | 5.0   | 345  | 0.4149          | 0.8653   | 0.8645 |
  | 0.3283        | 6.0   | 414  | 0.3982          | 0.8664   | 0.8656 |
  | 0.3015        | 7.0   | 483  | 0.3958          | 0.8685   | 0.8676 |
  | 0.269         | 8.0   | 552  | 0.3888          | 0.8716   | 0.8712 |
  | 0.2366        | 9.0   | 621  | 0.3909          | 0.8747   | 0.8742 |
  | 0.2241        | 10.0  | 690  | 0.3991          | 0.8716   | 0.8707 |
  | 0.1972        | 11.0  | 759  | 0.3984          | 0.8727   | 0.8720 |
  | 0.1765        | 12.0  | 828  | 0.3940          | 0.8758   | 0.8753 |
  | 0.1582        | 13.0  | 897  | 0.4049          | 0.8779   | 0.8775 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  