readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: distilbert_sa_GLUE_Experiment_data_aug_stsb_192
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE STSB
        type: glue
        args: stsb
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.18387488801123847
  ---
  
  <!-- 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_data_aug_stsb_192
  
  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: 2.8747
  - Pearson: 0.1794
  - Spearmanr: 0.1839
  - Combined Score: 0.1816
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------:|:--------------:|
  | 1.2844        | 1.0   | 1259  | 2.8897          | 0.1809  | 0.1879    | 0.1844         |
  | 0.4862        | 2.0   | 2518  | 2.9860          | 0.1713  | 0.1773    | 0.1743         |
  | 0.3063        | 3.0   | 3777  | 2.8747          | 0.1794  | 0.1839    | 0.1816         |
  | 0.2133        | 4.0   | 5036  | 2.9659          | 0.1611  | 0.1665    | 0.1638         |
  | 0.1614        | 5.0   | 6295  | 3.0123          | 0.1717  | 0.1793    | 0.1755         |
  | 0.1289        | 6.0   | 7554  | 3.0058          | 0.1798  | 0.1900    | 0.1849         |
  | 0.1077        | 7.0   | 8813  | 3.0575          | 0.1648  | 0.1786    | 0.1717         |
  | 0.0921        | 8.0   | 10072 | 3.0590          | 0.1687  | 0.1758    | 0.1723         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  