readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: rubert-tiny2_best_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_best_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: 0.3902
  - Accuracy: 0.8727
  - F1: 0.8720
  - Precision: 0.8718
  - Recall: 0.8727
  
  ## 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=0.0001
  - lr_scheduler_type: linear
  - num_epochs: 40
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 1.3497        | 1.0   | 69   | 1.2944          | 0.5376   | 0.4665 | 0.6374    | 0.5376 |
  | 1.2023        | 2.0   | 138  | 1.0370          | 0.7056   | 0.6745 | 0.7458    | 0.7056 |
  | 0.9289        | 3.0   | 207  | 0.7437          | 0.8121   | 0.8082 | 0.8117    | 0.8121 |
  | 0.6932        | 4.0   | 276  | 0.5717          | 0.8445   | 0.8428 | 0.8434    | 0.8445 |
  | 0.5613        | 5.0   | 345  | 0.4888          | 0.8580   | 0.8572 | 0.8573    | 0.8580 |
  | 0.469         | 6.0   | 414  | 0.4401          | 0.8633   | 0.8625 | 0.8623    | 0.8633 |
  | 0.4176        | 7.0   | 483  | 0.4156          | 0.8653   | 0.8646 | 0.8644    | 0.8653 |
  | 0.3724        | 8.0   | 552  | 0.4001          | 0.8706   | 0.8700 | 0.8699    | 0.8706 |
  | 0.3427        | 9.0   | 621  | 0.3972          | 0.8706   | 0.8698 | 0.8701    | 0.8706 |
  | 0.3243        | 10.0  | 690  | 0.3898          | 0.8737   | 0.8729 | 0.8736    | 0.8737 |
  | 0.3039        | 11.0  | 759  | 0.3887          | 0.8716   | 0.8710 | 0.8717    | 0.8716 |
  | 0.2803        | 12.0  | 828  | 0.3841          | 0.8716   | 0.8709 | 0.8709    | 0.8716 |
  | 0.264         | 13.0  | 897  | 0.3872          | 0.8758   | 0.8753 | 0.8758    | 0.8758 |
  | 0.2607        | 14.0  | 966  | 0.3837          | 0.8747   | 0.8743 | 0.8741    | 0.8747 |
  | 0.2437        | 15.0  | 1035 | 0.3893          | 0.8716   | 0.8710 | 0.8712    | 0.8716 |
  | 0.2358        | 16.0  | 1104 | 0.3867          | 0.8695   | 0.8691 | 0.8690    | 0.8695 |
  | 0.2278        | 17.0  | 1173 | 0.3886          | 0.8737   | 0.8732 | 0.8732    | 0.8737 |
  | 0.2143        | 18.0  | 1242 | 0.3902          | 0.8727   | 0.8720 | 0.8718    | 0.8727 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  