readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - clinc_oos
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-distilled-clinc
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: clinc_oos
        type: clinc_oos
        args: plus
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9332258064516129
    - task:
        type: text-classification
        name: Text Classification
      dataset:
        name: clinc_oos
        type: clinc_oos
        config: small
        split: test
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8587272727272727
        verified: true
      - name: Precision Macro
        type: precision
        value: 0.8619245385984416
        verified: true
      - name: Precision Micro
        type: precision
        value: 0.8587272727272727
        verified: true
      - name: Precision Weighted
        type: precision
        value: 0.8797945801452213
        verified: true
      - name: Recall Macro
        type: recall
        value: 0.9359690949227375
        verified: true
      - name: Recall Micro
        type: recall
        value: 0.8587272727272727
        verified: true
      - name: Recall Weighted
        type: recall
        value: 0.8587272727272727
        verified: true
      - name: F1 Macro
        type: f1
        value: 0.8922503214655346
        verified: true
      - name: F1 Micro
        type: f1
        value: 0.8587272727272727
        verified: true
      - name: F1 Weighted
        type: f1
        value: 0.8506829426037475
        verified: true
      - name: loss
        type: loss
        value: 0.9798759818077087
        verified: true
  ---
  
  <!-- 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. -->
  
  # distilbert-base-uncased-distilled-clinc
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1259
  - Accuracy: 0.9332
  
  ## 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: 2e-05
  - train_batch_size: 48
  - eval_batch_size: 48
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 7
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 318  | 0.5952          | 0.7355   |
  | 0.7663        | 2.0   | 636  | 0.3130          | 0.8742   |
  | 0.7663        | 3.0   | 954  | 0.2024          | 0.9206   |
  | 0.3043        | 4.0   | 1272 | 0.1590          | 0.9235   |
  | 0.181         | 5.0   | 1590 | 0.1378          | 0.9303   |
  | 0.181         | 6.0   | 1908 | 0.1287          | 0.9329   |
  | 0.1468        | 7.0   | 2226 | 0.1259          | 0.9332   |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  