readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: mobilebert_sa_GLUE_Experiment_logit_kd_stsb
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE STSB
        type: glue
        config: stsb
        split: validation
        args: stsb
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.1859084530305037
  ---
  
  <!-- 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_GLUE_Experiment_logit_kd_stsb
  
  This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE STSB dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1918
  - Pearson: 0.1864
  - Spearmanr: 0.1859
  - Combined Score: 0.1862
  
  ## 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: 128
  - eval_batch_size: 128
  - seed: 10
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 1.7465        | 1.0   | 45   | 1.2026          | 0.0588  | 0.0666    | 0.0627         |
  | 1.079         | 2.0   | 90   | 1.4599          | 0.0595  | 0.0691    | 0.0643         |
  | 1.0784        | 3.0   | 135  | 1.2063          | 0.0611  | 0.0707    | 0.0659         |
  | 0.9943        | 4.0   | 180  | 1.3534          | 0.0730  | 0.0730    | 0.0730         |
  | 0.9523        | 5.0   | 225  | 1.3943          | 0.1080  | 0.1010    | 0.1045         |
  | 0.8379        | 6.0   | 270  | 1.1918          | 0.1864  | 0.1859    | 0.1862         |
  | 0.7217        | 7.0   | 315  | 1.2542          | 0.2080  | 0.2144    | 0.2112         |
  | 0.6304        | 8.0   | 360  | 1.2209          | 0.1920  | 0.1979    | 0.1950         |
  | 0.5573        | 9.0   | 405  | 1.2925          | 0.1881  | 0.1814    | 0.1847         |
  | 0.5048        | 10.0  | 450  | 1.3943          | 0.1731  | 0.1877    | 0.1804         |
  | 0.4754        | 11.0  | 495  | 1.3058          | 0.1845  | 0.1817    | 0.1831         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  