readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - massive
  metrics:
  - accuracy
  model-index:
  - name: bert-tiny-Massive-intent-KD-BERT_and_distilBERT
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: massive
        type: massive
        config: en-US
        split: train
        args: en-US
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8470241023118544
  ---
  
  <!-- 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. -->
  
  # bert-tiny-Massive-intent-KD-BERT_and_distilBERT
  
  This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the massive dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3729
  - Accuracy: 0.8470
  
  ## 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: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 33
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 15.1159       | 1.0   | 720   | 12.8257         | 0.2253   |
  | 12.9949       | 2.0   | 1440  | 10.9891         | 0.4304   |
  | 11.3865       | 3.0   | 2160  | 9.5622          | 0.5032   |
  | 10.0553       | 4.0   | 2880  | 8.3700          | 0.5539   |
  | 8.9431        | 5.0   | 3600  | 7.4127          | 0.6104   |
  | 8.0135        | 6.0   | 4320  | 6.6185          | 0.6286   |
  | 7.1987        | 7.0   | 5040  | 5.9517          | 0.6818   |
  | 6.5168        | 8.0   | 5760  | 5.3879          | 0.7118   |
  | 5.9352        | 9.0   | 6480  | 4.9426          | 0.7275   |
  | 5.4299        | 10.0  | 7200  | 4.5637          | 0.7413   |
  | 5.0017        | 11.0  | 7920  | 4.2379          | 0.7585   |
  | 4.5951        | 12.0  | 8640  | 3.9699          | 0.7678   |
  | 4.2849        | 13.0  | 9360  | 3.7416          | 0.7737   |
  | 3.991         | 14.0  | 10080 | 3.5502          | 0.7865   |
  | 3.7455        | 15.0  | 10800 | 3.4090          | 0.7900   |
  | 3.5315        | 16.0  | 11520 | 3.3053          | 0.7914   |
  | 3.345         | 17.0  | 12240 | 3.1670          | 0.8003   |
  | 3.1767        | 18.0  | 12960 | 3.0739          | 0.8013   |
  | 3.0322        | 19.0  | 13680 | 2.9927          | 0.8047   |
  | 2.8864        | 20.0  | 14400 | 2.9366          | 0.8037   |
  | 2.7728        | 21.0  | 15120 | 2.8666          | 0.8091   |
  | 2.6732        | 22.0  | 15840 | 2.8146          | 0.8126   |
  | 2.5726        | 23.0  | 16560 | 2.7588          | 0.8195   |
  | 2.493         | 24.0  | 17280 | 2.7319          | 0.8273   |
  | 2.4183        | 25.0  | 18000 | 2.6847          | 0.8249   |
  | 2.3526        | 26.0  | 18720 | 2.6317          | 0.8323   |
  | 2.2709        | 27.0  | 19440 | 2.6071          | 0.8288   |
  | 2.2125        | 28.0  | 20160 | 2.5982          | 0.8323   |
  | 2.1556        | 29.0  | 20880 | 2.5546          | 0.8337   |
  | 2.1042        | 30.0  | 21600 | 2.5278          | 0.8318   |
  | 2.054         | 31.0  | 22320 | 2.5005          | 0.8411   |
  | 2.0154        | 32.0  | 23040 | 2.4891          | 0.8347   |
  | 1.9785        | 33.0  | 23760 | 2.4633          | 0.8367   |
  | 1.9521        | 34.0  | 24480 | 2.4451          | 0.8421   |
  | 1.9247        | 35.0  | 25200 | 2.4370          | 0.8416   |
  | 1.8741        | 36.0  | 25920 | 2.4197          | 0.8446   |
  | 1.8659        | 37.0  | 26640 | 2.4081          | 0.8406   |
  | 1.8367        | 38.0  | 27360 | 2.3979          | 0.8426   |
  | 1.8153        | 39.0  | 28080 | 2.3758          | 0.8451   |
  | 1.7641        | 40.0  | 28800 | 2.3729          | 0.8470   |
  | 1.7608        | 41.0  | 29520 | 2.3683          | 0.8460   |
  | 1.7647        | 42.0  | 30240 | 2.3628          | 0.8446   |
  | 1.7656        | 43.0  | 30960 | 2.3492          | 0.8470   |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  