readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - massive
  metrics:
  - accuracy
  model-index:
  - name: bert-tiny-Massive-intent-KD-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: 0.8396458435809149
  ---
  
  <!-- 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-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: 1.6612
  - Accuracy: 0.8396
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 10.9795       | 1.0   | 720   | 9.3236          | 0.2917   |
  | 9.4239        | 2.0   | 1440  | 7.9792          | 0.4092   |
  | 8.2632        | 3.0   | 2160  | 6.9824          | 0.4811   |
  | 7.3425        | 4.0   | 2880  | 6.1545          | 0.5514   |
  | 6.56          | 5.0   | 3600  | 5.4829          | 0.6060   |
  | 5.9032        | 6.0   | 4320  | 4.8994          | 0.6463   |
  | 5.3078        | 7.0   | 5040  | 4.4129          | 0.6911   |
  | 4.819         | 8.0   | 5760  | 4.0152          | 0.7073   |
  | 4.3866        | 9.0   | 6480  | 3.6734          | 0.7324   |
  | 3.9954        | 10.0  | 7200  | 3.3729          | 0.7516   |
  | 3.6764        | 11.0  | 7920  | 3.1251          | 0.7600   |
  | 3.3712        | 12.0  | 8640  | 2.9077          | 0.7752   |
  | 3.1037        | 13.0  | 9360  | 2.7361          | 0.7787   |
  | 2.8617        | 14.0  | 10080 | 2.5791          | 0.7860   |
  | 2.6667        | 15.0  | 10800 | 2.4383          | 0.7944   |
  | 2.476         | 16.0  | 11520 | 2.3301          | 0.7944   |
  | 2.3203        | 17.0  | 12240 | 2.2099          | 0.8052   |
  | 2.1698        | 18.0  | 12960 | 2.1351          | 0.8101   |
  | 2.0563        | 19.0  | 13680 | 2.0554          | 0.8111   |
  | 1.9294        | 20.0  | 14400 | 2.0100          | 0.8190   |
  | 1.8304        | 21.0  | 15120 | 1.9566          | 0.8210   |
  | 1.7315        | 22.0  | 15840 | 1.9076          | 0.8224   |
  | 1.6587        | 23.0  | 16560 | 1.8511          | 0.8283   |
  | 1.5876        | 24.0  | 17280 | 1.8230          | 0.8298   |
  | 1.5173        | 25.0  | 18000 | 1.8002          | 0.8259   |
  | 1.4676        | 26.0  | 18720 | 1.7667          | 0.8278   |
  | 1.3956        | 27.0  | 19440 | 1.7512          | 0.8313   |
  | 1.3436        | 28.0  | 20160 | 1.7233          | 0.8298   |
  | 1.3031        | 29.0  | 20880 | 1.6802          | 0.8318   |
  | 1.2584        | 30.0  | 21600 | 1.6768          | 0.8328   |
  | 1.2233        | 31.0  | 22320 | 1.6612          | 0.8396   |
  | 1.1884        | 32.0  | 23040 | 1.6608          | 0.8352   |
  | 1.1374        | 33.0  | 23760 | 1.6195          | 0.8387   |
  | 1.1299        | 34.0  | 24480 | 1.5969          | 0.8377   |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  