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_256
    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: 0.016625925233910453
  ---
  
  <!-- 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_256
  
  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: 1.1337
  - Pearson: 0.0151
  - Spearmanr: 0.0166
  - Combined Score: 0.0159
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 2.075         | 1.0   | 45   | 1.1337          | 0.0151  | 0.0166    | 0.0159         |
  | 1.0752        | 2.0   | 90   | 1.1691          | 0.0603  | 0.0648    | 0.0626         |
  | 1.0435        | 3.0   | 135  | 1.2035          | 0.0659  | 0.0746    | 0.0703         |
  | 1.0472        | 4.0   | 180  | 1.1488          | 0.0764  | 0.0817    | 0.0790         |
  | 0.9687        | 5.0   | 225  | 1.5234          | 0.0979  | 0.0959    | 0.0969         |
  | 0.9016        | 6.0   | 270  | 1.2243          | 0.1434  | 0.1381    | 0.1408         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  