readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: mobilebert_sa_GLUE_Experiment_data_aug_stsb_256
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE STSB
        type: glue
        args: stsb
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.1663132925626873
  ---
  
  <!-- 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_data_aug_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: 2.7922
  - Pearson: 0.1559
  - Spearmanr: 0.1663
  - Combined Score: 0.1611
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------:|:--------------:|
  | 1.0735        | 1.0   | 2518  | 2.8241          | 0.1664  | 0.1853    | 0.1759         |
  | 0.6303        | 2.0   | 5036  | 2.7922          | 0.1559  | 0.1663    | 0.1611         |
  | 0.501         | 3.0   | 7554  | 3.0939          | 0.1590  | 0.1630    | 0.1610         |
  | 0.3527        | 4.0   | 10072 | 3.2284          | 0.1662  | 0.1715    | 0.1689         |
  | 0.255         | 5.0   | 12590 | 2.9106          | 0.1775  | 0.1835    | 0.1805         |
  | 0.194         | 6.0   | 15108 | 3.1703          | 0.1550  | 0.1626    | 0.1588         |
  | 0.1563        | 7.0   | 17626 | 2.9109          | 0.1632  | 0.1691    | 0.1661         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  