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_128
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE STSB
        type: glue
        args: stsb
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.19841990187987396
  ---
  
  <!-- 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_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: 2.7704
  - Pearson: 0.1811
  - Spearmanr: 0.1984
  - Combined Score: 0.1898
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------:|:--------------:|
  | 1.1017        | 1.0   | 2518  | 2.7704          | 0.1811  | 0.1984    | 0.1898         |
  | 0.654         | 2.0   | 5036  | 3.0506          | 0.1580  | 0.1703    | 0.1642         |
  | 0.5737        | 3.0   | 7554  | 3.1679          | 0.1482  | 0.1569    | 0.1526         |
  | 0.4954        | 4.0   | 10072 | 3.3175          | 0.1564  | 0.1617    | 0.1590         |
  | 0.3722        | 5.0   | 12590 | 2.9558          | 0.1426  | 0.1517    | 0.1471         |
  | 0.276         | 6.0   | 15108 | 3.2021          | 0.1462  | 0.1530    | 0.1496         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  