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: 0.3546
  - Accuracy: 0.9325
  - F1: 0.9328
  - Precision: 0.9359
  - Recall: 0.9325
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.0686        | 1.0   | 12   | 0.2931          | 0.9141   | 0.9142 | 0.9163    | 0.9141 |
  | 0.0269        | 2.0   | 24   | 0.2690          | 0.9448   | 0.9444 | 0.9449    | 0.9448 |
  | 0.0282        | 3.0   | 36   | 0.3140          | 0.9141   | 0.9140 | 0.9168    | 0.9141 |
  | 0.0185        | 4.0   | 48   | 0.2977          | 0.9571   | 0.9570 | 0.9576    | 0.9571 |
  | 0.0103        | 5.0   | 60   | 0.3368          | 0.9264   | 0.9265 | 0.9296    | 0.9264 |
  | 0.0088        | 6.0   | 72   | 0.3067          | 0.9387   | 0.9385 | 0.9389    | 0.9387 |
  | 0.0152        | 7.0   | 84   | 0.3660          | 0.9264   | 0.9263 | 0.9282    | 0.9264 |
  | 0.0315        | 8.0   | 96   | 0.3793          | 0.9325   | 0.9328 | 0.9359    | 0.9325 |
  | 0.0258        | 9.0   | 108  | 0.3546          | 0.9325   | 0.9328 | 0.9359    | 0.9325 |
  
  
  ### Framework versions
  
  - Transformers 4.19.4
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  