readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilrubert_tiny-2nd-finetune-epru
    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-2nd-finetune-epru
  
  This model is a fine-tuned version of [mmillet/distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented](https://huggingface.co/mmillet/distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4467
  - Accuracy: 0.8712
  - F1: 0.8718
  - Precision: 0.8867
  - Recall: 0.8712
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.4947        | 1.0   | 12   | 0.4142          | 0.8773   | 0.8777 | 0.8907    | 0.8773 |
  | 0.2614        | 2.0   | 24   | 0.3178          | 0.9018   | 0.9011 | 0.9069    | 0.9018 |
  | 0.2079        | 3.0   | 36   | 0.3234          | 0.8773   | 0.8784 | 0.8850    | 0.8773 |
  | 0.1545        | 4.0   | 48   | 0.3729          | 0.8834   | 0.8830 | 0.8946    | 0.8834 |
  | 0.1028        | 5.0   | 60   | 0.2964          | 0.9018   | 0.9016 | 0.9073    | 0.9018 |
  | 0.0986        | 6.0   | 72   | 0.2971          | 0.9141   | 0.9139 | 0.9152    | 0.9141 |
  | 0.0561        | 7.0   | 84   | 0.3482          | 0.8957   | 0.8962 | 0.9023    | 0.8957 |
  | 0.0336        | 8.0   | 96   | 0.3731          | 0.8957   | 0.8953 | 0.9014    | 0.8957 |
  | 0.0364        | 9.0   | 108  | 0.4467          | 0.8712   | 0.8718 | 0.8867    | 0.8712 |
  
  
  ### Framework versions
  
  - Transformers 4.20.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  