readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: mobilebert_add_GLUE_Experiment_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: 0.08315656124877865
  ---
  
  <!-- 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_add_GLUE_Experiment_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: 2.3720
  - Pearson: 0.0872
  - Spearmanr: 0.0832
  - Combined Score: 0.0852
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 3.5023        | 1.0   | 45   | 2.4151          | 0.0290  | 0.0235    | 0.0262         |
  | 2.148         | 2.0   | 90   | 2.4051          | 0.0483  | 0.0436    | 0.0460         |
  | 2.1403        | 3.0   | 135  | 2.7281          | 0.0523  | 0.0502    | 0.0513         |
  | 2.0908        | 4.0   | 180  | 2.5970          | 0.0511  | 0.0509    | 0.0510         |
  | 2.0699        | 5.0   | 225  | 2.5728          | 0.0601  | 0.0621    | 0.0611         |
  | 2.0307        | 6.0   | 270  | 2.4059          | 0.0700  | 0.0781    | 0.0740         |
  | 1.9823        | 7.0   | 315  | 2.3720          | 0.0872  | 0.0832    | 0.0852         |
  | 1.9283        | 8.0   | 360  | 2.4539          | 0.0836  | 0.0814    | 0.0825         |
  | 1.9014        | 9.0   | 405  | 2.3975          | 0.0950  | 0.0915    | 0.0932         |
  | 1.883         | 10.0  | 450  | 2.6096          | 0.0894  | 0.0876    | 0.0885         |
  | 1.8453        | 11.0  | 495  | 2.4121          | 0.0970  | 0.0912    | 0.0941         |
  | 1.8275        | 12.0  | 540  | 2.6028          | 0.1038  | 0.0920    | 0.0979         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  