readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented
    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_single_finetuned_on_cedr_augmented
  
  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: 0.5908
  - Accuracy: 0.8653
  - F1: 0.8656
  - Precision: 0.8665
  - Recall: 0.8653
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.9172        | 1.0   | 69   | 0.5124          | 0.8246   | 0.8220 | 0.8271    | 0.8246 |
  | 0.4709        | 2.0   | 138  | 0.4279          | 0.8528   | 0.8505 | 0.8588    | 0.8528 |
  | 0.3194        | 3.0   | 207  | 0.3770          | 0.8737   | 0.8727 | 0.8740    | 0.8737 |
  | 0.2459        | 4.0   | 276  | 0.3951          | 0.8685   | 0.8682 | 0.8692    | 0.8685 |
  | 0.1824        | 5.0   | 345  | 0.4005          | 0.8831   | 0.8834 | 0.8841    | 0.8831 |
  | 0.1515        | 6.0   | 414  | 0.4356          | 0.8800   | 0.8797 | 0.8801    | 0.8800 |
  | 0.1274        | 7.0   | 483  | 0.4642          | 0.8727   | 0.8726 | 0.8731    | 0.8727 |
  | 0.0833        | 8.0   | 552  | 0.5226          | 0.8633   | 0.8627 | 0.8631    | 0.8633 |
  | 0.073         | 9.0   | 621  | 0.5327          | 0.8695   | 0.8686 | 0.8692    | 0.8695 |
  | 0.0575        | 10.0  | 690  | 0.5908          | 0.8653   | 0.8656 | 0.8665    | 0.8653 |
  
  
  ### Framework versions
  
  - Transformers 4.19.3
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  