readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: mobilebert_sa_GLUE_Experiment_stsb_128
    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: 0.22304777472582654
  ---
  
  <!-- 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_stsb_128
  
  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: 2.2718
  - Pearson: 0.2225
  - Spearmanr: 0.2230
  - Combined Score: 0.2228
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 5.1866        | 1.0   | 45   | 2.5161          | -0.0355 | -0.0329   | -0.0342        |
  | 2.1786        | 2.0   | 90   | 2.3527          | 0.0407  | 0.0395    | 0.0401         |
  | 2.1136        | 3.0   | 135  | 2.3101          | 0.0543  | 0.0555    | 0.0549         |
  | 2.1           | 4.0   | 180  | 2.4469          | 0.0624  | 0.0656    | 0.0640         |
  | 1.9564        | 5.0   | 225  | 2.8646          | 0.0815  | 0.0817    | 0.0816         |
  | 1.8611        | 6.0   | 270  | 2.5597          | 0.1089  | 0.1054    | 0.1071         |
  | 1.6702        | 7.0   | 315  | 2.7087          | 0.1644  | 0.1666    | 0.1655         |
  | 1.385         | 8.0   | 360  | 2.2718          | 0.2225  | 0.2230    | 0.2228         |
  | 1.2518        | 9.0   | 405  | 2.4105          | 0.2134  | 0.2022    | 0.2078         |
  | 1.143         | 10.0  | 450  | 2.5834          | 0.1998  | 0.2083    | 0.2040         |
  | 1.0191        | 11.0  | 495  | 2.6132          | 0.1856  | 0.1896    | 0.1876         |
  | 0.9431        | 12.0  | 540  | 2.8187          | 0.1784  | 0.1872    | 0.1828         |
  | 0.8725        | 13.0  | 585  | 2.8360          | 0.1815  | 0.1879    | 0.1847         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  