readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilrubert-tiny-cased-conversational-v1_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. -->
  
  # distilrubert-tiny-cased-conversational-v1_best_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: 0.5751
  - Accuracy: 0.8716
  - F1: 0.8713
  - Precision: 0.8721
  - Recall: 0.8716
  
  ## 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: 0.0001
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.8851        | 1.0   | 69   | 0.4740          | 0.8361   | 0.8346 | 0.8364    | 0.8361 |
  | 0.4404        | 2.0   | 138  | 0.4018          | 0.8643   | 0.8625 | 0.8672    | 0.8643 |
  | 0.305         | 3.0   | 207  | 0.3754          | 0.8800   | 0.8795 | 0.8794    | 0.8800 |
  | 0.2441        | 4.0   | 276  | 0.3942          | 0.8758   | 0.8748 | 0.8752    | 0.8758 |
  | 0.1837        | 5.0   | 345  | 0.4005          | 0.8873   | 0.8870 | 0.8877    | 0.8873 |
  | 0.1573        | 6.0   | 414  | 0.4468          | 0.8716   | 0.8718 | 0.8730    | 0.8716 |
  | 0.1292        | 7.0   | 483  | 0.4582          | 0.8747   | 0.8750 | 0.8758    | 0.8747 |
  | 0.0949        | 8.0   | 552  | 0.5110          | 0.8601   | 0.8601 | 0.8628    | 0.8601 |
  | 0.0729        | 9.0   | 621  | 0.5415          | 0.8674   | 0.8674 | 0.8681    | 0.8674 |
  | 0.058         | 10.0  | 690  | 0.5751          | 0.8716   | 0.8713 | 0.8721    | 0.8716 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  