readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilrubert-tiny-cased-conversational-v1_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. -->
  
  # distilrubert-tiny-cased-conversational-v1_finetuned_emotion_experiment_augmented_anger_fear
  
  This model is a fine-tuned version of [DeepPavlov/distilrubert-tiny-cased-conversational-v1](https://huggingface.co/DeepPavlov/distilrubert-tiny-cased-conversational-v1) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3760
  - Accuracy: 0.8758
  - F1: 0.8750
  - Precision: 0.8753
  - Recall: 0.8758
  
  ## 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: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 1.2636        | 1.0   | 69   | 1.0914          | 0.6013   | 0.5599 | 0.5780    | 0.6013 |
  | 1.029         | 2.0   | 138  | 0.9180          | 0.6514   | 0.6344 | 0.6356    | 0.6514 |
  | 0.904         | 3.0   | 207  | 0.8235          | 0.6827   | 0.6588 | 0.6904    | 0.6827 |
  | 0.8084        | 4.0   | 276  | 0.7272          | 0.7537   | 0.7477 | 0.7564    | 0.7537 |
  | 0.7242        | 5.0   | 345  | 0.6435          | 0.7860   | 0.7841 | 0.7861    | 0.7860 |
  | 0.6305        | 6.0   | 414  | 0.5543          | 0.8173   | 0.8156 | 0.8200    | 0.8173 |
  | 0.562         | 7.0   | 483  | 0.4860          | 0.8392   | 0.8383 | 0.8411    | 0.8392 |
  | 0.5042        | 8.0   | 552  | 0.4474          | 0.8528   | 0.8514 | 0.8546    | 0.8528 |
  | 0.4535        | 9.0   | 621  | 0.4213          | 0.8580   | 0.8579 | 0.8590    | 0.8580 |
  | 0.4338        | 10.0  | 690  | 0.4106          | 0.8591   | 0.8578 | 0.8605    | 0.8591 |
  | 0.4026        | 11.0  | 759  | 0.4064          | 0.8622   | 0.8615 | 0.8632    | 0.8622 |
  | 0.3861        | 12.0  | 828  | 0.3874          | 0.8737   | 0.8728 | 0.8733    | 0.8737 |
  | 0.3709        | 13.0  | 897  | 0.3841          | 0.8706   | 0.8696 | 0.8701    | 0.8706 |
  | 0.3592        | 14.0  | 966  | 0.3841          | 0.8716   | 0.8709 | 0.8714    | 0.8716 |
  | 0.3475        | 15.0  | 1035 | 0.3834          | 0.8737   | 0.8728 | 0.8732    | 0.8737 |
  | 0.3537        | 16.0  | 1104 | 0.3805          | 0.8727   | 0.8717 | 0.8722    | 0.8727 |
  | 0.3317        | 17.0  | 1173 | 0.3775          | 0.8747   | 0.8739 | 0.8741    | 0.8747 |
  | 0.323         | 18.0  | 1242 | 0.3759          | 0.8727   | 0.8718 | 0.8721    | 0.8727 |
  | 0.3327        | 19.0  | 1311 | 0.3776          | 0.8758   | 0.8750 | 0.8756    | 0.8758 |
  | 0.3339        | 20.0  | 1380 | 0.3760          | 0.8758   | 0.8750 | 0.8753    | 0.8758 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  