readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilrubert-tiny-2ndfinetune-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-2ndfinetune-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: 0.2085
  - Accuracy: 0.9333
  - F1: 0.9319
  - Precision: 0.9336
  - Recall: 0.9333
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.4825        | 1.0   | 13   | 0.2988          | 0.8848   | 0.8827 | 0.9056    | 0.8848 |
  | 0.2652        | 2.0   | 26   | 0.2435          | 0.9212   | 0.9216 | 0.9282    | 0.9212 |
  | 0.168         | 3.0   | 39   | 0.2120          | 0.9515   | 0.9501 | 0.9524    | 0.9515 |
  | 0.1593        | 4.0   | 52   | 0.1962          | 0.9333   | 0.9330 | 0.9366    | 0.9333 |
  | 0.1294        | 5.0   | 65   | 0.1855          | 0.9333   | 0.9334 | 0.9355    | 0.9333 |
  | 0.1065        | 6.0   | 78   | 0.1780          | 0.9394   | 0.9393 | 0.9399    | 0.9394 |
  | 0.0908        | 7.0   | 91   | 0.1967          | 0.9394   | 0.9388 | 0.9388    | 0.9394 |
  | 0.0432        | 8.0   | 104  | 0.2085          | 0.9333   | 0.9319 | 0.9336    | 0.9333 |
  
  
  ### Framework versions
  
  - Transformers 4.19.3
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  