readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wikitext
  metrics:
  - accuracy
  model-index:
  - name: mobilebert_sa_pre-training-complete
    results:
    - task:
        name: Masked Language Modeling
        type: fill-mask
      dataset:
        name: wikitext wikitext-103-raw-v1
        type: wikitext
        config: wikitext-103-raw-v1
        split: validation
        args: wikitext-103-raw-v1
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.7161816392520737
  ---
  
  <!-- 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. -->
  
  # mobilebert_sa_pre-training-complete
  
  This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the wikitext wikitext-103-raw-v1 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3239
  - Accuracy: 0.7162
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 10
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - training_steps: 300000
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Accuracy |
  |:-------------:|:-----:|:------:|:---------------:|:--------:|
  | 1.6028        | 1.0   | 7145   | 1.4525          | 0.6935   |
  | 1.5524        | 2.0   | 14290  | 1.4375          | 0.6993   |
  | 1.5323        | 3.0   | 21435  | 1.4194          | 0.6993   |
  | 1.5191        | 4.0   | 28580  | 1.4110          | 0.7027   |
  | 1.5025        | 5.0   | 35725  | 1.4168          | 0.7014   |
  | 1.4902        | 6.0   | 42870  | 1.3931          | 0.7012   |
  | 1.4813        | 7.0   | 50015  | 1.3738          | 0.7057   |
  | 1.4751        | 8.0   | 57160  | 1.4237          | 0.6996   |
  | 1.4689        | 9.0   | 64305  | 1.3969          | 0.7047   |
  | 1.4626        | 10.0  | 71450  | 1.3916          | 0.7068   |
  | 1.4566        | 11.0  | 78595  | 1.3686          | 0.7072   |
  | 1.451         | 12.0  | 85740  | 1.3811          | 0.7060   |
  | 1.4478        | 13.0  | 92885  | 1.3598          | 0.7092   |
  | 1.4441        | 14.0  | 100030 | 1.3790          | 0.7054   |
  | 1.4379        | 15.0  | 107175 | 1.3794          | 0.7066   |
  | 1.4353        | 16.0  | 114320 | 1.3609          | 0.7102   |
  | 1.43          | 17.0  | 121465 | 1.3685          | 0.7083   |
  | 1.4278        | 18.0  | 128610 | 1.3953          | 0.7036   |
  | 1.4219        | 19.0  | 135755 | 1.3756          | 0.7085   |
  | 1.4197        | 20.0  | 142900 | 1.3597          | 0.7090   |
  | 1.4169        | 21.0  | 150045 | 1.3673          | 0.7061   |
  | 1.4146        | 22.0  | 157190 | 1.3753          | 0.7073   |
  | 1.4109        | 23.0  | 164335 | 1.3696          | 0.7082   |
  | 1.4073        | 24.0  | 171480 | 1.3563          | 0.7092   |
  | 1.4054        | 25.0  | 178625 | 1.3712          | 0.7103   |
  | 1.402         | 26.0  | 185770 | 1.3528          | 0.7113   |
  | 1.4001        | 27.0  | 192915 | 1.3367          | 0.7123   |
  | 1.397         | 28.0  | 200060 | 1.3508          | 0.7118   |
  | 1.3955        | 29.0  | 207205 | 1.3572          | 0.7117   |
  | 1.3937        | 30.0  | 214350 | 1.3566          | 0.7095   |
  | 1.3901        | 31.0  | 221495 | 1.3515          | 0.7117   |
  | 1.3874        | 32.0  | 228640 | 1.3445          | 0.7118   |
  | 1.386         | 33.0  | 235785 | 1.3611          | 0.7097   |
  | 1.3833        | 34.0  | 242930 | 1.3502          | 0.7087   |
  | 1.3822        | 35.0  | 250075 | 1.3657          | 0.7108   |
  | 1.3797        | 36.0  | 257220 | 1.3576          | 0.7108   |
  | 1.3793        | 37.0  | 264365 | 1.3472          | 0.7106   |
  | 1.3763        | 38.0  | 271510 | 1.3323          | 0.7156   |
  | 1.3762        | 39.0  | 278655 | 1.3325          | 0.7145   |
  | 1.3748        | 40.0  | 285800 | 1.3243          | 0.7138   |
  | 1.3733        | 41.0  | 292945 | 1.3218          | 0.7170   |
  | 1.3722        | 41.99 | 300000 | 1.3074          | 0.7186   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  