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_256
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE STSB
        type: glue
        args: stsb
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.1803916738510789
  ---
  
  <!-- 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_256
  
  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: 2.9014
  - Pearson: 0.1788
  - Spearmanr: 0.1804
  - Combined Score: 0.1796
  
  ## 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  | Combined Score | Validation Loss | Pearson | Spearmanr |
  |:-------------:|:-----:|:-----:|:--------------:|:---------------:|:-------:|:---------:|
  | 1.1748        | 1.0   | 1259  | 0.1811         | 3.0220          | 0.1788  | 0.1834    |
  | 0.4365        | 2.0   | 2518  | 0.1777         | 2.9725          | 0.1774  | 0.1779    |
  | 0.2502        | 3.0   | 3777  | 0.1796         | 2.9014          | 0.1788  | 0.1804    |
  | 0.1669        | 4.0   | 5036  | 3.1989         | 0.1510          | 0.1571  | 0.1540    |
  | 0.1237        | 5.0   | 6295  | 2.9701         | 0.1717          | 0.1765  | 0.1741    |
  | 0.0969        | 6.0   | 7554  | 3.1938         | 0.1479          | 0.1523  | 0.1501    |
  | 0.0802        | 7.0   | 8813  | 3.2793         | 0.1350          | 0.1440  | 0.1395    |
  | 0.0669        | 8.0   | 10072 | 3.1238         | 0.1564          | 0.1640  | 0.1602    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  