readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: distilbert_sa_GLUE_Experiment_logit_kd_data_aug_stsb
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE STSB
        type: glue
        args: stsb
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.19929870493761834
  ---
  
  <!-- 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. -->
  
  # distilbert_sa_GLUE_Experiment_logit_kd_data_aug_stsb
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE STSB dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.5182
  - Pearson: 0.1994
  - Spearmanr: 0.1993
  - Combined Score: 0.1993
  
  ## 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: 256
  - eval_batch_size: 256
  - 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
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 0.3603        | 1.0   | 1259 | 1.5492          | 0.1887  | 0.2052    | 0.1969         |
  | 0.0731        | 2.0   | 2518 | 1.5182          | 0.1994  | 0.1993    | 0.1993         |
  | 0.0347        | 3.0   | 3777 | 1.5924          | 0.1665  | 0.1770    | 0.1717         |
  | 0.0232        | 4.0   | 5036 | 1.5826          | 0.1596  | 0.1673    | 0.1635         |
  | 0.0178        | 5.0   | 6295 | 1.5555          | 0.1812  | 0.1747    | 0.1779         |
  | 0.0158        | 6.0   | 7554 | 1.5487          | 0.1878  | 0.1877    | 0.1878         |
  | 0.0139        | 7.0   | 8813 | 1.6483          | 0.1789  | 0.1730    | 0.1759         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  